Evaluation harnesses
Automated test suites that score your AI on faithfulness, relevance, and safety — so quality is proven before launch and re-checked on every change.
- Golden test datasets
- Faithfulness & safety scoring
- Regression gates in CI
AI Governance & Security
AI governance & security that makes AI safe to ship
We put the controls, evidence, and guardrails around your AI that turn an impressive demo into a system you can responsibly deploy — measured for quality, protected against misuse and data leaks, and fully auditable. The result is AI your customers, your security team, and your regulators can all trust, so you can move fast on AI without betting the business on it.
The challenge
Unmanaged AI is a risk waiting to surface
The same models that unlock new value can also hallucinate, repeat biased or unsafe content, and leak the sensitive data you feed them. A single confident-but-wrong answer can mislead a customer; a single leaked record can trigger a breach. Without evaluation you can't prove quality, and without an audit trail you can't explain a decision after the fact or show how a model reached it. Attackers are learning to exploit this too, using crafted prompts to override instructions or pull data out of the system. And as regulation like the EU AI Act and security standards like SOC 2 tighten, "it works in the demo" is no longer enough to put AI in front of customers — or past your own risk and legal teams.
The risks we close
- Unverified outputs
Hallucinated or biased answers nobody is measuring.
- Prompt injection
Crafted inputs that hijack the model or exfiltrate data.
- Sensitive-data exposure
PII and confidential data leaking into prompts or logs.
- No traceability
No record of what the AI did, or why, when asked.
What we build
The controls that make AI safe to deploy
Governance isn't a document on a shelf — it's working software around your model, wired into the same pipeline that serves your users. We build the four layers that keep AI measurable, guarded, traceable, and compliant, and hand them over so your team can own and extend them.
Guardrails & PII protection
Input and output filters that block unsafe, off-policy, or injected content and redact sensitive data before it ever reaches a model or a log.
- Prompt-injection defense
- PII detection & redaction
- Content & policy filters
Audit trails & observability
Every prompt, response, and tool call captured and traceable — with monitoring and alerts so you can explain any decision and catch drift early.
- Request & response logging
- Tracing & cost tracking
- Drift & anomaly alerts
Compliance & policy frameworks
Responsible-AI policies mapped to the standards that apply to you — turning regulatory obligations into concrete, testable controls your team can evidence on demand.
- Risk classification
- Acceptable-use policies
- EU AI Act & SOC 2 mapping
Why it works
Confidence backed by evidence
We treat governance as engineering, not paperwork — so the safety of your AI is something you can measure, demonstrate, and defend instead of merely promise. Each control produces evidence you can point to when someone asks how you know the system is safe.
- Measurable quality
Evaluation harnesses turn "we think it's good" into scores you can track release over release.
- Safe & guarded
Guardrails block unsafe outputs, prompt injection, and data exfiltration before they reach a user.
- Fully auditable
A complete trail of what the AI did and why, ready for users, auditors, and regulators.
- Compliance-ready
Controls mapped to the standards you answer to, producing the evidence those frameworks expect.
What you get
- Eval dashboards
Quality and safety scores you can watch over time.
- Guardrail policies
Documented, enforced rules for inputs and outputs.
- Audit logs
Traceable records of every prompt, response, and action.
- Governance playbook
The policies and runbooks your team can own and extend.
Technologies
Governance built on a proven stack
We use established evaluation, guardrail, and observability tooling rather than reinventing it — and stay model-agnostic across OpenAI, Anthropic Claude, and open-weight models so the controls fit your accuracy, cost, and privacy needs.
How we work
From AI risk to AI you can trust
1
Assess
We review your AI use case, data flows, and exposure to find where it can fail, leak, or fall foul of regulation, and rank the risks by likelihood and impact.
2
Define policy
We classify the risk and write the responsible-AI policies and acceptable-use rules your system must enforce, in plain language your whole team can follow.
3
Implement
We build the evaluation harness, guardrails, PII protection, and audit logging directly into your AI pipeline, with regression gates so controls hold on every release.
4
Monitor
We run continuous evals and observability in production, with dashboards and alerts so quality drift, abuse, and incidents surface early — before users feel them.
Industries
Governance tuned to your domain
Fintech & Banking
Healthcare & Life Sciences
Retail & E-commerce
EdTech & SaaS
FAQ
AI governance questions
What is AI governance?
AI governance is the set of policies, controls, and evidence that keep an AI system safe, accurate, and accountable in production. In practice it means defining what the system is allowed to do, measuring its quality, guarding its inputs and outputs, and keeping a record of what it did — so you can deploy AI with confidence and answer to users, auditors, and regulators.
How do you stop hallucinations and unsafe outputs?
We combine retrieval grounding with output guardrails and an evaluation harness. Answers are tied to your source data with citations, guardrails block off-policy or unsafe responses and prompt-injection attempts, and the eval suite scores faithfulness and relevance before launch and on every change — so quality is measured, not assumed.
How do you protect sensitive data and PII?
We detect and redact PII before it reaches a model, apply access control so the system only sees data a user is entitled to, and log every request and response in an audit trail. Where needed we keep data in your environment and choose models and providers that meet your privacy and residency requirements.
Can you help with AI compliance (e.g. EU AI Act, SOC 2)?
Yes. We map your AI use case to the relevant obligations — such as the EU AI Act's risk tiers or SOC 2 controls — then implement the policies, guardrails, evaluations, and audit logging that produce the evidence those frameworks expect. We are engineers, not your lawyers, so we work alongside your legal and compliance teams.