❯Engagement tiers
Pick a pilot to de-risk a single workflow, a production engagement to gate the whole portfolio, or a compliance audit when something is already shipping.
Single-domain readiness probe before a production rollout. Calibrate one workflow against your accuracy, latency, and cost targets.
End-to-end methodology transfer for teams shipping AI agents to business-critical processes. Evaluation, monitoring, and audit lineage in one engagement.
Standalone assessment for systems already in production. Evidence pack matched to the format your assessor expects, signed and time-stamped.
❯Methodology
The phases below are the through-line of every engagement. Pilot tiers compress phases 04–05; audits enter at phase 03.
PHASE 01
Workflow inventory, domain rubric capture, threat model, and the accuracy / latency / cost envelope your stakeholders will sign against.
PHASE 02
Domain-expert review of the test corpus, prompt families, and pass/fail thresholds. Every prompt traceable to the rubric that produced it.
PHASE 03
Jailbreak, prompt-injection, and exfiltration probes against staging. Regressions captured as permanent tests in your suite.
PHASE 04
Drift monitors, regression gates, and audit lineage wired into your CI and observability stack. Runbooks for the on-call team.
PHASE 05
Quarterly suite refresh, incident-driven corpus updates, and assessor-ready audit packs exported on demand.
❯Deliverables
Engagements end with the methodology in your repository, not in our heads. Every artefact below ships under your version control, gated by your CI.
A repository of test prompts, expected behaviours, and scoring rubrics — checked into your monorepo, owned by your team after hand-off.
Statistical alerts on output distributions, latency envelopes, and cost-per-token, integrated with your existing on-call and incident tooling.
Curated jailbreak, injection, and exfiltration prompts refreshed weekly from public disclosures and your own incident telemetry.
Signed, time-stamped lineage for every inference: prompt, retrieved context, model, parameters, decision, and reviewer — exportable for GDPR, HIPAA, and SOC 2 reviews.
Incident playbooks for refusal-rate inversion, p95 latency creep, distribution shift on embeddings, and provider-side weight refreshes.
❯Operating commitments
❯Procurement questions
We are vendor-neutral. Engagements have shipped against Claude, GPT, Gemini, and self-hosted open-source models — with cascading routing across providers when cost or latency targets demand it. We do not recommend models based on marketing material; the evaluation rubric decides.
No. Customer data is never used to train models, and is never shared between engagements. Telemetry stays inside your perimeter; we operate with zero retention by default.
Every engagement includes a control-mapping matrix to the assessor's framework, plus inference lineage signed and time-stamped at write. Audit packs export in the format your reviewer already expects.
Yes. Production engagements run inside the customer's cloud account; only the evaluation suite source and tooling cross the boundary. Air-gapped variants are available for regulated workloads.
A pilot is successful when stakeholders can sign on the accuracy, latency, and cost envelope; when the adversarial probe surfaces no production-blocking failure modes; and when the team owns the suite well enough to extend it without us.
Open-source frameworks give you scaffolding. We deliver the calibrated rubrics, the adversarial corpus, the drift monitors, and the audit lineage that production systems are graded on. The methodology is the deliverable; the tooling is how it ships.