Accelerate adoption and productivity gains of AI-augmented development through automation, governance, and end-to-end analytics

AI-assisted development is everywhere

Artificial Intelligence (AI) has been around for a while and is growing faster than ever, with new tools helping developers generate code more quickly than ever. A recent survey found that 92% of US developers are using AI coding tools both in and outside of work.* Despite the proliferation of generative AI tools many organizations are still attempting to find ways to manage AI’s use in augmenting code. This newfound coding speed has the potential to revolutionize software delivery by dramatically increasing productivity and accelerating release velocity, but these gains are not automatic. Implementing strong governance over release pipelines influenced by AI, and establishing baselines while quantifying gains is essential.

Using AI to generate code comes with risks, but it's also something businesses can't ignore

As AI-augmented code becomes increasingly indispensable, the need for proper governance, guardrails, and improved delivery processes grows. Downstream impacts must be mitigated to increase the SDLC's efficiency enough to handle the high volume of code. This is important as generative AI models usually have very little oversight making it increasingly likely that AI-augmented code contains security and vulnerability issues. If left unchecked, those issues can lead to regulatory and compliance concerns which can cost an enterprise both financially and in brand reputation. Even if these challenges are solved organizations are left with the task of pouring over their data to quantify productivity and show value in the company’s investment in AI tooling.

The solution lies in teams adopting more automation to improve the quality, security, and overall delivery of their AI-augmented code. Proper code governance is also a must to reduce risk and ensure compliance and auditability. Qualifying gains and establishing baselines will increase productivity by identifying risks and discovering bottlenecks which will allow teams to continuously improve their software delivery processes.


  • Security and vulnerability: AI models may be trained on harmful data, leaving it open for vulnerabilities
  • Regulations and compliance: AI-augmented code can contain biases and might not protect user data
  • Quantifying ROI of AI: It is hard to isolate the impact of AI generated code and translate that into benefits.

The AI-powered DevSecOps
platform enables enterprises to accelerate
their SDLC with end-to-end automation to
meet the increased speed of AI generated code.

We manage security, quality and compliance
risk with built-in governance and policy
enforcement , that enables organizations to
adopt Copilots confidently.

Our end-to-end intelligence increases
productivity by allowing organizations to
quantify gains, identify improvement areas,
and predict risk.

-AI's impact on the developer experience

Quantify gains, identify improvements and predict risks

Accelerate software delivery

Adopt further automation and AI to turn increased code creation into business value with improved quality security and overall delivery. Measure the impact of AI-assisted code on engineering teams’ productivity. Going beyond lines of code written gives key insights that help identify potential bottlenecks and areas of improvement. Combine data from your existing DevOps tooling to provide a clear view of productivity across teams and applications, allowing leaders to make data-driven decisions to optimize software development and reduce risk.

Govern release pipelines

Govern and control AI-generated code via built-in governance and policy enforcement to reduce risk. Empower engineering teams to take advantage of AI-Augmented code while still maintaining control. Embed governance and compliance standards into workflows to ensure audit and traceability across software delivery. Leverage pre-defined, standardized templates and integrate platform engineering practices to further streamline adoption across engineering.

Increase delivery productivity

Accelerate adoption and productivity gains of AI-augmented development continuous improvement and faster risk identification. Go beyond baselining and measuring developer productivity by expanding productivity insights across all software delivery. Provide end-to-end visibility allowing clear measurement of risks and benefits. Benchmark development improvements via analytics such as DORA and Flow Acceleration while predicting risk of change, bottlenecks, and quality.

The Difference

One platform that automates release pipelines and integrates complex toolchains. Unify app delivery, integrate existing tools & scale across any environment.

Automated mobile app testing and security designed to scale. Provide secure, high-quality apps with reduced risk through testing & threat monitoring insights.

Built-in AI, intelligence, compliance, and governance across all software delivery workflows. Centralize data, optimize processes, and gain augmented insights for faster, safer software delivery. AI-powered DevSecOps platform

Predictive Intelligence Diagram

About is an industry-leading technology company dedicated to helping Global 5000 enterprises achieve digital transformation goals. The company’s AI-powered DevSecOps platform unifies, secures, and generates predictive insights across the software lifecycle. empowers organizations to scale software development teams, continuously deliver software with greater quality and security while uncovering new market opportunities and enhancing business value through smarter software investments.

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