We are pleased to announce that Typo has successfully achieved SOC 2 Type II certification, a significant milestone in our ongoing commitment to security excellence and data protection. This certification reflects our dedication to implementing and maintaining the highest standards of security controls to protect our customers' valuable development data.
SOC 2 (Service Organization Control 2) is a framework developed by the American Institute of Certified Public Accountants (AICPA) that establishes comprehensive standards for managing customer data based on five "trust service criteria": security, availability, processing integrity, confidentiality, and privacy.
The distinction between Type I and Type II certification is substantial. While Type I examines whether a company's security controls are suitably designed at a specific point in time, Type II requires a more rigorous evaluation of these controls over an extended period—typically 6-12 months. This provides a more thorough verification that our security practices are not only well-designed but consistently operational.
For organizations relying on Typo's software engineering intelligence platform, this certification delivers several meaningful benefits:
The SOC 2 Type II report represents a comprehensive assessment of Typo's security infrastructure and practices. This independent verification covers several critical dimensions of our security program:
Achieving SOC 2 Type II certification required a comprehensive effort across our organization and consisted of several key phases:
We began with a thorough assessment of our existing security controls against SOC 2 requirements, identifying areas for enhancement. This systematic gap analysis was essential for establishing a clear roadmap toward certification, particularly regarding our integration capabilities that connect with customers' sensitive development environments.
Based on our assessment findings, we implemented enhanced security measures across multiple domains:
A distinguishing feature of Type II certification is the requirement to demonstrate consistent adherence to security controls over time. This necessitated implementing robust monitoring systems and conducting regular internal audits to ensure sustained compliance with SOC 2 standards.
The final phase involved a thorough examination by an independent CPA firm, which conducted a comprehensive assessment of our security controls and their operational effectiveness over the specified period. Their verification confirmed our adherence to the rigorous standards required for SOC 2 Type II certification.
We understand that many organizations need to review our security practices as part of their vendor assessment process. To request our SOC 2 Type II report:
Our team will respond within two business days with next steps, which may include a standard non-disclosure agreement to protect the confidential information contained in the report.
The comprehensive report provides detailed information about our control environment, risk assessment methodologies, control activities, information and communication systems, and monitoring procedures—all independently evaluated by third-party auditors.
While achieving SOC 2 Type II certification marks an important milestone, we recognize that security is a continuous journey rather than a destination. As the threat landscape evolves, so too must our security practices.
Our ongoing security initiatives include:
These efforts underscore our enduring commitment to protecting the development data our customers entrust to us.
At Typo, we believe that robust security is foundational to delivering effective developer analytics that engineering teams can confidently rely upon. Our SOC 2 Type II certification demonstrates our commitment to protecting your valuable data while providing the insights your development teams need to excel.
By choosing Typo, organizations gain not only powerful development analytics but also a partner dedicated to maintaining the highest standards of security and compliance—particularly important for teams operating in regulated environments with stringent requirements.
We appreciate the trust our customers place in us and remain committed to maintaining and enhancing the security controls that protect your development data. If you have questions about our security practices or SOC 2 certification, please contact us at hello@typoapp.io.
Tired of code reviews disrupting your workflow? As developers know, pull request reviews are crucial for software quality, but they often lead to context switching and time-consuming interruptions. Tools that provide irrelevant suggestions often become background noise for reviewers, further complicating the process. That’s why Typo is excited to announce a powerful new feature designed to empower reviewers: AI-Generated PR Summaries with Estimated Time to Review Label. Typo is an AI powered PR reviews solution and a code review tool that automates and enhances the review process, helping you catch issues faster and improve code quality. This feature is built to minimize interruptions, save time, and ultimately, make your life as a reviewer significantly easier.
Imagine knowing exactly how much time a pull request (PR) will take to review. No more guessing, no more unexpected time sinks. Typo’s Estimated Time to Review Labels provide a clear, data-driven estimate of the review effort required. Typo analyzes code changes, file complexity, changed files, and the number of lines modified to generate an accurate review time estimate.
These features help reviewers prioritize their workload and focus on the most critical PRs, ultimately saving time and streamlining the review process.
Time is a precious commodity for developers. Typo’s AI-Generated PR Summaries provide a concise and insightful overview of code changes, allowing reviewers to quickly grasp the key modifications without wading through every line of code. Unlike tools that show just the diff, Typo's summaries deliver deeper context by analyzing the entire codebase and highlighting the significance of each change.
Typo's summaries create less noise by focusing on the most relevant changes, helping reviewers avoid unnecessary alerts and distractions. They also help reviewers quickly spot minor issues that might otherwise be overlooked, ensuring that even small, subtle problems are addressed early.
For example, a PR summary generated by Typo might read: "Refactored the authentication module to improve error handling and fixed a minor issue with token expiration logic. No breaking changes detected. Updated documentation for new API endpoints." This highlights key changes and potential issues, making the review process more efficient.
These two features work together to create a more efficient and less disruptive code review process. Typo focuses on enabling effective code reviews by automating and enhancing the reviewing process, ensuring that teams can catch more issues and collaborate better. Unlike traditional manual code reviews, Typo's automation streamlines the workflow, reducing bottlenecks and increasing efficiency.
The best automated tools should support security and code quality standards, especially for high-compliance teams. Typo helps enforce code standards and allows teams to set specific rules for their review workflow, ensuring consistency and adherence to best practices. It also supports maintaining and generating documentation and PR documentation, making it easier to keep project records up to date.
Typo can help identify edge cases, ensuring robust code quality and preventing hard-to-find bugs. Additionally, Typo can assist with generating or checking unit tests as part of the review process. Compared to other tools, Typo offers unique advantages such as AI-powered summaries and intelligent issue detection. Typo is suitable for both open source projects and private repositories, with flexible pricing and access options to fit different organizational needs.
By providing time estimates and AI-powered summaries, Typo empowers reviewers to:
The strategic implementation of AI-powered code review tools within GitHub's ecosystem fundamentally transforms the traditional code review methodology into a sophisticated, streamlined operational framework that leverages advanced machine learning capabilities. Clean integration with GitHub or GitLab helps maintain momentum in the review process. This comprehensive integration involves embedding AI-generated analytical summaries and contextual feedback mechanisms directly within GitHub's pull request infrastructure, which enables development teams to access critical insights and actionable recommendations without disrupting their established workflow patterns or requiring migration to external platforms.
Such seamless integration optimizes and streamlines the entire code review process by automating routine analysis tasks, thereby allowing development teams to significantly reduce the temporal investment required for manual review procedures while simultaneously focusing their expertise on enhancing overall code quality, maintainability, and architectural consistency. Through the deployment of review tools that operate natively within GitHub's collaborative environment, every pull request benefits from comprehensive automated feedback systems that analyze code patterns, detect potential vulnerabilities, and suggest improvements, ultimately making the review process considerably faster, more consistent in its application of standards, and substantially less disruptive to the development workflow. As a direct result of this technological integration, development teams can maintain stringent quality standards while ensuring their continuous integration and deployment pipelines operate with optimal efficiency, all while harnessing the transformative power of artificial intelligence to enhance and evolve their code review methodologies.
AI-driven summarization capabilities establish comprehensive integration pathways with established pull request methodologies through GitHub's sophisticated infrastructure, delivering advanced artificial intelligence frameworks directly into code evaluation workflows. Upon pull request initialization, these sophisticated analytical systems dive into code modification patterns, systematically examine critical alterations, and autonomously generate comprehensive summaries that precisely identify potential software defects and security vulnerability vectors.
Human code reviewers receive comprehensive, actionable intelligence and complete contextual understanding for each pull request submission, empowering them to execute well-informed decisions with enhanced velocity and unwavering confidence. Through the strategic incorporation of auto-generated analytical summaries into the comprehensive review methodology, development teams can ensure that every code modification undergoes thorough systematic evaluation, while simultaneously reducing the manual computational overhead required for each individual review cycle. This sophisticated integration between AI-powered analytical frameworks and the pull request evaluation process not only accelerates comprehensive review timelines but also substantially elevates the overall software quality standards and security posture of your entire codebase infrastructure.
Direct integration of AI-powered code review tools with GitHub fundamentally transforms the software development workflow by implementing sophisticated analysis algorithms that examine code commits, pull requests, and repository patterns. Selecting the right tool involves evaluating how it integrates with CI/CD processes. These intelligent systems leverage machine learning models trained on vast datasets of code repositories to identify potential vulnerabilities, architectural inconsistencies, and adherence violations to established coding standards.
Automated code review mechanisms utilize large language models (LLM) to analyze code comments, commit messages, and documentation, while simultaneously applying static analysis techniques to detect subtle bugs, security vulnerabilities, and performance bottlenecks before they propagate to production environments. By implementing rule-based engines and machine learning algorithms, AI-driven tools ensure consistent enforcement of coding guidelines across development teams, analyzing historical code patterns and team practices to establish baseline standards that align with organizational best practices. Advanced features including incremental analysis capabilities, comprehensive test coverage evaluation algorithms, and customizable rule configuration frameworks enable development teams to implement tailored review processes that optimize both code quality metrics and development velocity through intelligent automation.
Leveraging AI within the code review ecosystem significantly reduces cognitive overhead by automating repetitive analysis tasks, minimizing context switching between development environments, and generating actionable insights through predictive algorithms that analyze code complexity patterns and potential failure points. This intelligent automation enables developers to allocate cognitive resources toward complex problem-solving activities such as advanced debugging methodologies, architectural decision-making, and innovative feature development strategies.
AI-powered systems generate comprehensive pull request summaries using natural language generation techniques, create detailed impact analyses through dependency graph analysis, and produce contextual documentation that facilitates efficient reviewer comprehension and accelerates approval workflows. These capabilities enhance cross-functional collaboration by providing standardized communication protocols, reducing information asymmetry between team members, and establishing consistent review quality regardless of reviewer experience levels or domain expertise.
Whether implementing solutions for small-scale prototype applications or enterprise-level distributed systems, integrating AI-powered code review tools represents a paradigm shift in development methodology that fundamentally enhances software quality assurance processes. Development teams experience measurable improvements in code quality metrics, substantial reduction in manual review overhead, and increased confidence in release stability through comprehensive automated analysis frameworks.
Advanced capabilities including automated release documentation generation, sophisticated issue detection algorithms utilizing pattern recognition, and contextual feedback systems that adapt to project-specific requirements enable teams to establish proactive quality gates that identify potential issues during early development phases while maintaining rigorous standards throughout the software development lifecycle. As the technological landscape continues evolving toward increasingly complex distributed architectures and accelerated delivery cycles, adopting AI-powered code review methodologies becomes essential for organizations seeking to optimize development workflows, enhance code quality assurance processes, and maintain competitive advantage in rapidly evolving software engineering environments.
Typo helps developers maintain focus and save time, even when faced with incoming PR reviews. Proper setup and learning curves for AI tools should be minimal for successful integration into development workflows. This ensures that developers can quickly adapt to new tools without significant disruptions to their productivity.
Try Typo today and experience the benefits of AI-powered time estimates and summaries. Streamline your processes, boost productivity, and empower your development team.
In an ever-evolving tech world, organisations need to innovate quickly while keeping up high standards of quality and performance. The key to achieving these goals is empowering engineering leaders with the right tools and technologies.
Typo is a software intelligence platform that optimizes software delivery by identifying real-time bottlenecks in SDLC, automating code reviews, and measuring developer experience. We aim to help organizations ship reliable software faster and build high-performing teams.
However, engineering leaders often struggle to bridge the divide between traditional management practices and modern software development leading to missed opportunities for growth, ineffective team dynamics, and slower progress in achieving organizational goals.
To address this gap, we launched groCTO, a community designed specifically for engineering leaders.
Effective engineering leadership is crucial for building high-performing teams and driving innovation. However, many leaders face significant challenges and gaps that hinder their effectiveness. The role of an engineering leader is both demanding and essential. From aligning teams with strategic goals to managing complex projects and fostering a positive culture, they have a lot on their plates. Hence, leaders need to have the right direction and support so they can navigate the challenges and guide their teams efficiently.
Here’s when groCTO comes in!
groCTO is a community designed to empower engineering managers on their leadership journey. The aim is to help engineering leaders evolve, navigate complex technical challenges, and drive innovative solutions to create groundbreaking software. Engineering leaders can connect, learn, and grow to enhance their capabilities and, in turn, the performance of their teams.
Over 73% of successful tech leaders believe having a mentor is key to their success.
At groCTO, we recognize mentorship as a powerful tool for addressing leadership challenges and offering personalised support and fresh perspectives. That’s why we’ve kept Connect a cornerstone of our community - offering 1:1 mentorship sessions with global tech leaders and CTOs. With over 74 mentees and 20 mentors, our Connect program fosters valuable relationships and supports your growth as a tech leader.
These sessions allow emerging leaders to:
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To keep our tech community informed and inspired, groCTO brings you a fresh set of learning resources every week:
Are you a tech coach looking to make an impact?
At groCTO, we are committed to making this community bigger and better. We want current and aspiring engineering leaders to invest in their growth as well as contribute to pushing the boundaries of what engineering teams can achieve.
We’re just getting started. A few of our future plans for groCTO include:
We envision a community that thrives on continuous engagement and growth. Scaling our resources and expanding our initiatives, we want to ensure that every member of groCTO finds the support and knowledge they need to excel.
At Typo, our vision is clear: to ship reliable software faster and build high-performing engineering teams. With groCTO, we are making significant progress toward this goal by empowering engineering leaders with the tools and support they need to excel.
Join us in this exciting new chapter and be a part of a community that empowers tech leaders to excel and innovate.
We’d love to hear from you! For more information about groCTO and how to get involved, write to us at hello@grocto.dev
Dev teams hold great importance in the engineering organization. They are essential for building high-quality software products, fostering innovation, and driving the success of technology companies in today’s competitive market. A strong engineering culture supports continuous learning, high-quality work, and collaboration, which are crucial for sustained growth. Tech companies leverage these principles, along with automation and standardized standards, to drive innovation and maximize developer productivity.
Adopting agile methodologies is a key strategy for engineering organizations aiming to optimize productivity and streamline development processes. Fostering a positive work environment is equally important, as high morale and job satisfaction among engineering teams are key indicators of a healthy and productive work environment, leading to increased developer satisfaction and overall productivity.
However, engineering leaders need to understand the bottlenecks holding them back. Since these blindspots can directly affect the projects. Hence, this is when software development analytics tools come to your rescue. And these analytics software stands better when they have various features and integrations, engineering leaders are usually looking out for.
Typo is an intelligent engineering platform that is used for gaining visibility, removing blockers, and maximizing developer effectiveness. Typo’s approach aligns with best practices recognized by the broader software development community, ensuring it meets the evolving needs of modern engineering teams. Let’s know more about why engineering leaders prefer to choose Typo as their important tool:
Typo represents an advanced engineering analytics platform architected to revolutionize software development methodologies by optimizing developer productivity metrics and comprehensive team performance indicators across distributed development environments. Through implementation of sophisticated measurement frameworks that analyze developer productivity in holistic and statistically significant approaches, Typo enables engineering leadership to execute data-driven strategic decisions that facilitate continuous improvement initiatives throughout organizational development ecosystems. Measuring software developer productivity is complex and should focus on outcomes and impact, not just output, to avoid the pitfalls of traditional metrics. The platform delivers comprehensive insights into critical performance indicators including deployment frequency metrics, code quality assessments, cyclomatic complexity analysis, and customer satisfaction correlation patterns, empowering technology organizations to optimize their software development life cycle processes and achieve measurable project delivery success.
By implementing advanced analytics algorithms that examine team collaboration dynamics, developer job satisfaction indices, and knowledge transfer efficiency metrics alongside traditional engineering performance indicators, Typo facilitates development teams in identifying bottlenecks, performance optimization opportunities, and workflow process streamlining initiatives. In addition to these analytics and metrics, Typo incorporates the SPACE framework—which evaluates developer productivity through five dimensions: Satisfaction and well-being, Performance, Activity, Communication and collaboration, and Efficiency and flow. The SPACE framework was developed by the same entities that created the DORA metrics, including researchers from GitHub and Microsoft. The DORA metrics are widely recognized for providing a good overview of software delivery performance, focusing on outcomes and impact. True engineering productivity is about impact, not just the sheer volume of code, and measuring productivity can sometimes lead to unintended consequences such as gaming the system. This comprehensive analytical approach ensures that software development organizations not only maintain high-quality code delivery standards but also cultivate positive collaborative development environments that enhance team cohesion and productivity scalability. Through Typo’s implementation, organizations can systematically improve overall productivity and overall team performance by focusing on these holistic frameworks, enhance developer productivity benchmarks, elevate customer satisfaction correlation metrics, and sustain competitive advantages within the rapidly evolving software development landscape through data-driven engineering excellence.
Engineering productivity metrics constitute the fundamental framework for evaluating how effectively development teams optimize value delivery throughout the software development lifecycle. For engineering leaders, measuring developer productivity transcends rudimentary quantitative approaches like counting lines of code or tracking temporal investments—it demands a comprehensive understanding of team dynamics, code quality assessments, and the intricate development workflow orchestration. By strategically leveraging sophisticated productivity metrics, engineering managers can extract actionable insights into team performance patterns, identify optimization opportunities across development phases, and execute data-driven decisions that facilitate continuous improvement initiatives.
Core metrics such as deployment frequency optimization, comprehensive code quality assessments, and the volume and efficiency analysis of pull request workflows provide a holistic perspective on how development teams collaborate to achieve strategic project objectives. Deployment frequency, for instance, directly reflects the cadence at which new features or critical fixes are delivered to end-users, serving as a primary indicator of a team's operational agility and market responsiveness capabilities. Code quality metrics ensure that accelerated delivery cycles do not compromise long-term maintainability standards or customer satisfaction benchmarks, while systematic pull request tracking provides comprehensive visibility into collaborative patterns and knowledge transfer mechanisms within development teams.
Measuring developer productivity presents inherent complexity, as it must simultaneously account for both the technical architecture considerations and human resource dynamics of software engineering operations. Effective engineering productivity metrics empower engineering managers to optimize resource allocation strategies, streamline workflow automation processes, and cultivate an organizational culture of continuous improvement and innovation. By strategically focusing on these critical performance indicators, organizations can enhance team operational efficiency, maintain elevated code quality standards across development cycles, and ultimately deliver superior outcomes that drive customer value and business objectives.
Engineering metrics are the measurements of engineering outputs and processes. However, there isn’t a pre-defined set of metrics that the software development teams use to measure to ensure success. This depends on various factors including team size, the background of the team members, and so on. Engineering productivity metrics and engineering productivity measures include a range of indicators such as cycle time, throughput, and quality, which help teams evaluate and track their efficiency.
Typo’s customized DORA (Deployment frequency, Change failure rate, Lead time, and Mean Time to Recover) key metrics and other engineering metrics can be configured in a single dashboard based on specific development processes. This helps benchmark the dev team’s performance and identifies real-time bottlenecks, sprint delays, and blocked PRs. Tracking productivity metrics and relevant metrics is essential to identify bottlenecks and optimize team performance. Software engineering productivity is best evaluated using outcome-focused metrics; while lines of code can indicate activity, they do not necessarily reflect productivity or quality. With the user-friendly interface and tailored integrations, engineering leaders can get all the relevant data within minutes and drive continuous improvement. Customer satisfaction scores are also valuable outcome metrics for engineering teams, similar to how sales and support teams measure their effectiveness.
Code review is all about improving the code quality. Maintaining code quality through regular and constructive code review cycles is essential to ensure high standards and continuous improvement in software development. It improves the software teams’ productivity and streamlines the development process. However, when done manually, the code review process can be time-consuming and takes a lot of effort. Typo helps automate repetitive tasks, streamlining processes and reducing manual effort, which ultimately boosts developer productivity.
Typo’s automated code review tool auto-analyses codebase and pull requests to find issues and auto-generates fixes before it merges to master. It understands the context of your code and quickly finds and fixes any issues accurately, making pull requests easy and stress-free. Linters and formatters like ESLint and Prettier catch syntax errors and inconsistent naming in real-time, while advanced tools like SonarQube & Typo's SAST detect deeper issues that might lead to logical errors or security vulnerabilities. Developers can minimize typo impact by using IDE features such as linting and autocomplete, and Integrated Development Environments (IDEs) like Visual Studio Code and IntelliJ IDEA provide syntax highlighting and auto-completion to catch errors in real time. It standardizes your code, reducing the risk of a software security breach and boosting maintainability, while also providing insights into code coverage and code complexity for thorough analysis.
While a burndown chart helps visually track progress of teams’ work, it is time-consuming and doesn’t provide insights about the specific types of issues or tasks. Hence, it is always advisable to complement it with sprint analysis tools to provide additional insights tailored to agile project management.
Typo has an effective sprint analysis feature that tracks and analyzes the team’s progress throughout a sprint. It uses data from Git and the issue management tool to provide insights into getting insights on how much work has been completed, how much work is still in progress, and how much time is left in the sprint. Version control systems are essential for tracking code changes and measuring active participation through commits and pull requests, which demonstrate ongoing development and collaboration. Understanding how software development teams work involves analyzing metrics related to effort, output, outcomes, and impact. This helps in identifying potential problems in the early stages, identifying areas where teams can be more efficient, and meeting deadlines. Additionally, these tools foster team collaboration by improving communication and coordination among team members.
When engineering metrics focus on individual success rather than team performance, it creates a sense of surveillance rather than support. This leads to decreased motivation, productivity, and trust among development teams. Instead, building productive teams and improving the team’s productivity by evaluating performance holistically is more effective. Holistic assessment frameworks like the SPACE framework provide a comprehensive understanding of team's productivity by considering multiple dimensions beyond just output. Hence, there are better ways to use the engineering metrics.
Typo has a metrics dashboard that focuses on the team’s health and performance. It lets engineering leaders compare the team’s results with what healthy benchmarks across industries look like and drive impactful initiatives for your team. The dashboard provides insights into engineering teams efficiency by tracking team-level metrics and deployment processes, such as the number of merged pull requests per week. The SPACE framework uses space metrics to evaluate satisfaction, performance, activity, communication, and efficiency, offering a more complete view of productivity. Since it considers only the team’s goals, it lets team members work together and solve problems together. Hence, fosters a healthier and more productive work environment conducive to innovation and growth.
Measuring developer experience not only focuses on quantitative metrics but also requires qualitative feedback as well. By prioritizing the human side of team members and developer productivity, engineering managers can create a more inclusive and supportive environment for them. Typo also supports work life balance by helping managers identify and address burnout risks, promoting flexible scheduling and regular breaks to reduce stress and prevent burnout.
Typo helps in getting a 360 view of the developer experience as it captures qualitative insights and provides an in-depth view of the real issues that need attention. With signals from work patterns and continuous AI-driven pulse check-ins on the experience of developers in the team, Typo helps with early indicators of their well-being and actionable insights on the areas that need your attention. It also tracks the work habits of developers across multiple activities, such as Commits, PRs, Reviews, Comments, Tasks, and Merges, over a certain period. If these patterns consistently exceed the average of other developers or violate predefined benchmarks, the system identifies them as being in the Burnout zone or at risk of burnout. Typo further encourages skill development by providing insights that highlight opportunities for training and continuous learning, supporting ongoing professional growth.
The more the tools can be integrated with software, the better it is for the software developers. It streamlines the development process, enforces standardization and consistency, and provides access to valuable resources and functionalities.
Typo lets you see the complete picture of your engineering health by seamlessly connecting to your tech tool stack. This includes:
Implementing Typo within engineering organizations involves a comprehensive integration process that seamlessly connects the platform to existing project management ecosystems, version control repositories, and essential software development infrastructure. Engineering leaders can leverage Typo’s advanced configuration capabilities to monitor critical performance indicators including pull request velocity, code review cycle times, deployment frequency metrics, and continuous integration pipeline efficiency. Typo provides complete visibility in software delivery, allowing teams to dive deep into key DORA metrics. This data-driven approach provides actionable insights into team velocity, resource utilization patterns, and overall development productivity benchmarks that directly impact software delivery outcomes.
To fully harness Typo’s sophisticated analytical capabilities, development teams must embrace agile development methodologies, implement automated workflow orchestration, and cultivate a data-driven culture of continuous improvement and iterative enhancement. Automating repetitive tasks is crucial to boost efficiency and productivity, freeing up time for software engineers to focus on higher-value work. By utilizing Typo’s AI-powered automated code review mechanisms and intelligent resource allocation algorithms, engineering organizations can systematically optimize development workflows, minimize technical debt accumulation, and significantly reduce overall development operational costs. The platform’s comprehensive metrics analysis framework, combined with active engagement from all stakeholders across the development lifecycle, enables teams to rapidly identify performance bottlenecks, detect patterns in development inefficiencies, and implement targeted optimization strategies that drive measurable improvements in software delivery capabilities.
Typo serves as a catalyst for engineering leadership in establishing robust development environments and fostering high-performance engineering cultures through enhanced cross-team collaboration, systematic knowledge transfer protocols, and transparent communication channels across distributed development teams. Fostering a positive engineering culture that supports continuous learning and high-quality work is essential, as is recognizing the role of software engineers in high-performing teams. Leveraging data-driven insights and proactive monitoring can lead to increased developer productivity and improved work environments. This comprehensive approach not only accelerates developer productivity and reduces time-to-market but also enhances end-user satisfaction and project success rates through improved software quality metrics. By strategically integrating Typo’s advanced analytics and automation capabilities into existing development workflows, software engineering teams can achieve unprecedented levels of operational efficiency, optimize resource allocation strategies, and establish sustainable competitive advantages in their engineering delivery capabilities.
Typo is a software delivery tool that can help ship reliable software faster. You can find real-time bottlenecks in your SDLC, automate code reviews, and measure developer experience – all in a single platform.
The G2 Summer 2023 report is out!
We are delighted to share that Typo ranks as a leader in the Software Development analytics tool category. A big thank you to all our customers who supported us in this journey and took the time to write reviews about their experience. It really got us motivated to keep moving forward and bring the best to the table in the coming weeks.
Typo is placed among the leaders in Software Development Analytics. Besides this, we earned the ‘User loved us’ badge as well.
Our wall of fame shines bright with –
Typo has been ranked a Leader in the Grid Report for Software Development Analytics Tool | Summer 2023. This is a testament to our continuous efforts toward building a product that engineering teams love to use.
The ratings also include –
We, as a team, achieved the feat of attaining the score of:
Check out what other users have to say about Typo here.
Typo is an intelligent AI-driven Engineering Management platform that enables modern software teams with visibility, insights & tools to code better, deploy faster & stay aligned with business goals.
Having launched with Product Hunt, we started with 15 engineers working with sheer hard work and dedication and have impacted 5000+ developers globally and engineering leaders globally, 400,000+ PRs & 1.5M+ commits.
We are NOT just the software delivery analytics platform. We go beyond the SDLC metrics to build an ecosystem that is a combination of intelligent insights, impactful actions & automated workflows – that will help Managers to lead better & developers perform better
As the first step, Typo gives core insights into dev velocity, quality & throughout that has helped the engineering leaders reduce their PR cycle time by almost 57% and 2X faster project deliveries.
Typo empowers continuous improvement in the developers & managers with goal setting & specific visibility to developers themselves.
The leaders can set goals to ensure best practices like PR sizes, avoid merging PRs without review, identify high-risk work & others. Typo nudges the key stakeholders on Slack as soon as the goal is breached. Typo also automates the workflow on Slack to help developers with faster PR shipping and code reviews.
Typo provides core insights to your developers that are 100% confidential to them. It helps developers to identify their strengths and core areas of improvement that have impacted the software delivery. It helps them gain visibility & measure the impact of their work on team efficiency & goals.
We believe that all three aspects – work, collaboration & well-being – need to fall in place to help an individual deliver their best. Inspired by the SPACE framework for developer productivity, we support Pulse Check-Ins, Developer Experience insights, Burnout predictions & Engineering surveys to paint a complete picture.
It’s all of your immense love and support that made us a leader in such a short period. We are grateful to you!
But this is just the beginning. Our aim has always been to level up your dev game and we will be coming with the new exciting releases in the next few weeks.
Interested in using Typo? Sign up for FREE today and get insights in 5 min.
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