Expert AI Quality Engineering, End to End.
NovaFlow AI provides two core service lines — both built around one principle: if it can't be deterministically verified, it doesn't ship.
Service 01
Agentic AI Benchmarking & Task Development
"Building the tests that frontier AI can't fake its way through."
We design and engineer production-grade benchmarking tasks for Terminal Bench-style evaluation frameworks — the standard used by leading AI research organizations to measure real-world agentic performance. Every task we build is a complete, self-contained evaluation environment: a precise instruction set, a containerized execution sandbox, a deterministic oracle solution, and a rigorous binary verification suite.
What's included:
- ✓Multi-step agentic task design across 15+ technical domains (software engineering, cybersecurity, data science, DevOps, and more)
- ✓Docker-based isolated execution environments with pinned dependencies and anti-cheat safeguards
- ✓Deterministic oracle solutions and binary pass/fail verification scripts
- ✓Difficulty calibration via simulation runs against GPT-5, Claude Sonnet 4.5, and other frontier models
- ✓Independent peer review and technical adjudication of submitted evaluation tasks
Service 02
Software Verification & AI Evaluation
"Making sure AI-generated code actually works — not just looks right."
We conduct end-to-end quality assurance on AI-generated software modifications, agentic task outputs, and LLM evaluation workflows for enterprise AI clients. Our work spans complex codebase analysis, regression testing, pull request review, and structured model performance evaluation — all delivered at premium engineering quality.
What's included:
- ✓In-depth review and debugging of complex, real-world software repositories modified by AI agents
- ✓Fail-to-Pass (F2P) and Pass-to-Pass (P2P) regression test suite development using Pytest and Jest
- ✓Blind agentic model performance evaluation and ranking using structured comparison frameworks
- ✓Pull request identification, screening, and classification for AI training dataset construction
- ✓Coding prompt engineering and model response evaluation across multiple technical domains
Technology Stack
The full range of tools and languages we work with
Languages
Testing
Infrastructure
AI & ML
Databases
Frontend
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