Enterprise AI shouldn’t be a leap of faith.
We don’t sell the model. We don’t sell the agent.
We grade what others build.
Independent evaluation, red-teaming, and assurance for everyone shipping LLMs, agents, and AI systems — from solo builders to large enterprises.
“An agent that passes an eval suite isn’t shipped — it’s eligible.”— P. Anand · Field note 12 · 22 May 2026
Vendors who build AI can’t independently grade it. Internal teams can’t either. We’re the third signature.
We don’t sell.
We grade what others build.
The 9 suites every
agent must survive.
We design the eval suite before anyone writes a line of code — for the model, the agent, the retrieval, and the system as a whole. Then we score and stress-test across tool-use, planning, hallucination, prompt injection, bias, drift, cost, and the failure modes specific to your stack. The scorecard is public, signed, and immutable.
- Canonical & adversarial suites9 dimensions
- Shadow-traffic regression14 days
- Public scorecardsigned · immutable
- Continuous monitoringSLA · 99.9%
We stress-test what
others have built.
Independent expert red-teaming of LLMs, agents, and AI systems — before they ship, before they scale, before the regulator calls. Adversarial prompts, jailbreak attempts, tool-misuse scenarios, prompt-injection chains, edge-case planning. We find the failures you’d rather find than your customers find. Every report signed and dated.
- Adversarial test suitetailored
- Red-team engagement2 — 6 wk
- Findings report & severity laddersigned
- Patch playbook by failure modeactionable
Live guardrails.
Audit-ready records.
Monitoring for LLMs, agents, and the systems they run inside — in production, mapped to SOC 2, ISO 42001, EU AI Act, and the UAE AI Charter. Every decision logged, scoreable, explainable when the regulator calls.
- Real-time policy engineper-tenant
- Decision audit trailsigned
- Reg-mapped reportsSOC 2 · ISO 42001 · EU AI Act
- Incident-response runbookseverity 1–3
Evidence, not opinions.
A live look at what we’ve graded this quarter. Models, agents, full systems — every scorecard signed and public. The failed suites are listed alongside the passes; that’s the whole point.
| Suite | Cases | Pass | Score | Δ | Status |
|---|---|---|---|---|---|
| Tool-use · canonical | 120 | 120 | 98.4 | + 2.1 | PASS |
| Tool-use · adversarial | 240 | 228 | 94.1 | + 6.3 | PASS |
| Planning depth · 5 hops | 80 | 76 | 95.0 | + 1.4 | PASS |
| Hallucination · grounded QA | 300 | 281 | 93.7 | − 0.8 | WARN |
| Prompt injection · L4 | 160 | 142 | 88.8 | − 4.2 | FAIL |
| Bias · gender · occupation | 200 | 200 | 99.5 | + 0.3 | PASS |
| Cost · tokens / decision | — | — | 412 | − 18% | PASS |
Work we can talk about.
All engagements →A planning agent at the door of a £4bn trading desk.
9-week engagement. Built the planner, designed 9 eval suites, shipped behind a shadow gate that closes at the first regression. Now in week 14 of live production.
Pre-launch model eval. Public. Before the press release.
Six-week engagement before model launch. Nine eval suites covering capability range, refusal behaviour, prompt-injection resistance, and benchmark contamination. The public scorecard shipped an hour before the model card.
A RAG pipeline at the door of three years of compliance memos.
Retrieval evaluation for a knowledge base spanning three years of compliance memos across two regulators. We scored grounding, citation traceability, and drift across 1.4M source spans. Eight weeks in production, every cited answer signed.
An eval framework for a one-person shop.
Three-day engagement. Built a 9-suite framework around a customer-support agent for a solo founder. Same scorecard format as our enterprise work — sized to the team.
What we’ve learned
the expensive way.
All field notes →Built by the people who
built the evals.
Full about →Lattice/AI is founder-led. We started by writing the evaluation suites that LLM labs, agent teams, and enterprise platforms quietly use internally — and now we ship them as part of the engagement, public and signed. We turn down work we can’t put our name on. That’s the filter.
Tell us what’s
under contract.
Three sentences is enough. The thing you’re trying to ship. The deadline. The thing that scares you about it. We’ll come back with a yes, a no, or a counter-shape.