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Open-Core Utility
The local testing driver (vantage-core) is open-source, free, and runs entirely in your local workspace using your own environment variables. No gated walls for core developer utilities.
Vantage RuntimeAI · About
Why we are building Vantage
The transition from stateless software to stateful AI requires a complete overhaul of the deployment pipeline.
Thesis
Traditional software engineering succeeded because it was deterministic: Input A always yielded Output B. Traditional QA frameworks, unit tests, and CI/CD gates were built entirely for this paradigm.
Generative AI agents break this model completely. A conversational agent might pass a single-turn unit test flawlessly in staging, only to suffer massive context dilution, drop compliance guardrails, and trigger exponential token cost spikes by Turn 15 in production.
We built Vantage because logging failures after they happen in live traffic is an operational failure. Engineering teams need automated, adversarial simulation infrastructure to map their model’s breaking points before their customers do.
Choosing a model or agent should not be marketing-driven. RuntimeAI is objective testing infrastructure — like a crash-test lab for agents. Run realistic scenarios in Sim, score them with deterministic rubrics, and decide with evidence: which model, whether to release, what monitoring is worth. Risk reduction and confidence for small decisions and big ones alike.
The product is built to integrate, not interrupt: the same check-rides run in the browser during design, via API before a model-selection or release review, and as exit-code gates in the CI pipeline you already merge through — built from your own schema, policy, and API context, not just a canned library. At merge time it can post a FinOps comment showing rubric result and estimated inference-cost delta, so engineering and finance see quality and spend on the same pull request. A proof, audit, and economics layer that works seamlessly inside existing thought and execution processes.
Scenarios span task execution (SQL, pipelines, ML readouts) and conversation work (support, sales, billing) — same rubrics across Sim, API, CI, and post-release monitoring.
Built for Production Realities
Vantage was co-founded by Simon Brightman, a veteran product, data, and analytics executive with over 20 years of hands-on experience architecting SaaS data platforms, data engineering pipelines, and complex enterprise monetization strategies.
As an active, hands on product, analytics and data engineering leader who has spent decades managing real-world compute telemetry, latency budgets, and compounding API costs, Simon built Vantage not out of an abstract research lab—but to fix a glaring operational blind spot in the modern generative deployment cycle.
Core principles
02
Hard Telemetry Only
We eliminate subjective “vibe checks.” Every simulation run outputs deterministic engineering metrics — scored with auditable rubrics, not LLM-as-judge: Guardrail Erosion Velocity, path-dependent token bloat, and P95 latency.
03
Native Integration
Drop vantage-core into GitHub Actions or GitLab CI as a regression gate — the bundled example exits 1 when guardrail erosion exceeds threshold. Cadence follows the use-case family: analytical suites gate every pull request, and conversational agents earn a quarterly full check plus weekly drift monitoring. Size ongoing cost on Cost Forecast.