context engineering — 2026
Vitoria Lima
for the love of agents
Your experts know what correct looks like.
Your agents don't — yet.
Head of ML
we finally know why agents fail in prod
Two lines of code. Every LLM call, tool use, and decision — captured across 15+ providers. Zero config.
liveRoute traces to the people who actually know — physicians, attorneys, analysts. Structured feedback, not thumbs up.
liveEvery trace links to the exact prompt, model, and tools that produced it. SHA-256 hashing, automatic.
liveDefine evaluation criteria per domain. Weighted scoring, conditional logic, multiple question types.
liveCTO
engineers and doctors finally speak the same language
Engineer Portal
Traces, agents, evals, deployments. Ship better context.
contexere
engineering portal
eng@acme-health.com
7 total traces
| trace id | user prompt | status | |
|---|---|---|---|
| tr-7f2a8c | Patient on Lisinopril with elevated K+ — safe to add spironolactone? | escalated | |
| tr-8b3c1d | Interpret HbA1c of 6.8% in context of recent steroid course | allowed | |
| tr-9d4e2f | Review non-compete clause in Section 7.2 | not sent | |
| tr-ae5f3a | Recommend imaging for persistent lower back pain, 3 weeks | allowed | |
| tr-bf6g4b | Enterprise plan pricing for 50-seat with HIPAA | allowed |
SME Portal
Review queue, structured feedback. No code — just judgment.
contexere
sme portal
dr.chen@acme.com
reviewing trace a3f8c21b · cardiac-triage-review
user prompt
agent response
Dr. Chen, Cardiologist
I just answer the questions — the agent gets smarter on its own
Models catch formatting errors. They miss the domain nuance that separates a safe answer from a correct one.
Catches surface errors. Hallucinates confidence. Cannot distinguish between an answer that sounds right and one that is right. Fine for demos.
Chief Medical Officer
our radiologists caught errors no model would
SME Lead
our expertise finally lives outside our heads
Transform what experts know but never wrote down into structured, versioned ground truth entries.
liveV1 is your upload. V4 has institutional knowledge. Each cycle compounds expert corrections.
liveCompare any two versions side-by-side. See what changed, who changed it, why.
liveOne click to fold expert corrections into your dataset from any eval run.
liveExperts keep flagging the same issue — Contexere identifies the pattern and writes the fix.
liveHard constraints extracted from expert corrections. "Never recommend imaging without symptom duration > 48h."
Run N rounds of self-correction: analyze failures, generate suggestions, create version, re-evaluate. Hands-off.
in progressReview each suggestion. Accept to auto-create a new agent version. Always in control.
liveML Engineer
it's like having a senior prompt engineer who never sleeps
10% → 50% → 100%. Automatic rollback on regression. No big-bang deploys.
in progressContinuous monitoring against ground truth. Quality drops → new eval cycle triggers automatically.
in progressNew context versions validated against historical traces. Only demonstrable improvements get promoted.
coming soonPrecision, recall, F1 tracked across every version. Full confusion matrix analysis.
coming sooncapture → evaluate → learn → synthesize → deploy
and again, automatically
the context your agents need
lives in your experts' heads
Contexere gets it out
Vitoria
building the future of agent context