Kept sharp, not left to drift.
AI degrades quietly as your data and the world change. We keep models and agents performing — and improving — on a standing cadence.
SFM.biz continuously tunes and hardens your AI: tracking performance, re-testing against new failure modes, updating prompts and models, and closing the gaps that open as your data and needs shift. The goal is a system that gets better over time instead of silently worse.
The problem, and how we handle it.
The problem
The dangerous failure isn't a crash, it's silent degradation. An agent that was accurate at launch drifts as inputs change and edge cases accumulate, and by the time users complain, it's been wrong for weeks.
How we handle it
We run a standing optimization cadence: performance monitoring, evaluation against real cases, prompt and model updates, and hardening against new failure modes, so the system stays accurate as the ground shifts.
What the engagement includes.
- Performance monitoring against real production cases
- Evaluation harness to catch regressions before users do
- Prompt and model updates as better options ship
- Hardening against newly discovered failure modes
- Improvement reporting so gains are visible
Let's keep your AI working.
A short conversation about what you're running, where it's drifting, and what it would take to have someone steady on the wheel.
Don't gamble on the flash. Rely on the experience.
FAQ
How do you know an agent is degrading?
We instrument it and evaluate against real cases on a cadence, so drift shows up in the numbers before it shows up in complaints.
Do you retrain models?
Where it helps. Often the bigger wins come from better prompting, retrieval, and guardrails, tuning is about the whole system, not just the model.
How often do you tune?
On a standing cadence matched to how fast your inputs change, plus reactively when monitoring flags a regression.
Is this only for agents SFM built?
No. We optimize whatever you're running, including systems built elsewhere.