We know what will go wrong. We fix it in the right order.

You are building a product that runs on LLMs and agents, and it has to ship. You need someone who has already seen the problem you are about to hit and can help you fix it with the right tooling, an adjusted approach, or a change of architecture, in weeks rather than quarters.

• A single crafted input can breach your product

  Prompt injection through a document, a web page or a tool response; data exfiltration through a tool call; an agent holding more permission than the feature needs: each one a security incident that costs customers and reputation, not a model quirk. We threat model the system you actually built and fix what architecture can fix, instead of patching it in the prompt.

• Your evaluations are your IP, and you do not have them yet

  Evals are what let you change a model, a prompt or a chain without guessing, and they have to answer three questions at once: does it do the job, does it stay reliable, does it hold under attack. We build that set from your real traffic and keep it running in CI.

• Your guardrails are deployed, not validated

  Every vendor sells a guardrail; most block your users, miss your attackers, and are never re-tested after the next prompt change. We tune the controls to your use case and put them under regression so a change cannot silently undo them.

• Your agents have privileged access and no identity

  Agents call tools, MCP servers and other agents with credentials never designed for non-human callers, so nobody can say which agent did what, on whose behalf. We put identity, permission and trust boundaries where the damage would happen, and the audit trail exists before someone asks for one.

• Cost and reliability break down at scale

  Spend that scales with usage instead of value, retries that mask failures, latency that loses users. We find the causes and fix both cost and reliability without a rewrite.

• Regulatory requirements block what you want to ship

  A customer's security review, an investor's diligence, an EU AI Act obligation: each one standing between a finished feature and shipping it. We tell you what applies, what does not, and the shortest defensible path through.

• Find-and-fix sprint

  You show us the system, we tell you the problems, then we fix the ones that matter, in order.

  You leave with: Working code, the fixes that mattered, and a ranked list of what is next.

  1 to 3 weeks

• Evaluations and guardrails build

  We build the evaluation set that tells you whether the system does the job, stays reliable and holds under attack, from your real traffic. Then we tune your guardrails against it.

  You leave with: The eval set running in CI, your guardrails under regression, and a team able to extend both.

  2 to 4 weeks

• Embedded security engineering

  One of us inside your team while you build, in the repos and the standups.

  You leave with: Reviews, evals, guardrails and threat modelling at the pace of your sprints, not after them.

  Part time, by the month

• Deep-tech advisory

  For the questions that block a decision: is this architecture safe, which vendor, what does the AI Act mean for us.

  You leave with: Answers from people who have built and broken these systems, when the decision is live.

  On call

Every engagement starts with a short discovery call and is scoped to what will actually reduce risk. Ask us for the investment ranges that match your setup.

You are bringing AI into systems that already run your business: documents, workflows, tools, customers. The risk surface that creates is specific to your organization, and generic controls rarely match it. We map it, and then turn it into controls your teams understand, test and own.

• Your AI can reach data your access model never approved

  RAG over internal documents, copilots with broad access, assistants that summarise what they should not see. We find the paths data takes through your AI systems and close the ones that should not exist.

• You cannot demonstrate that any of it behaves

  Pilots go to production on a demo and a hope, and nobody can show what the system does with your data, your edge cases or a hostile user. We build evaluations against your own content and make the results something you can put in front of a risk committee.

• Most of the AI inside your perimeter is not yours

  Vendor models, SaaS copilots, MCP servers and agents you did not build, plus the ones teams adopted without telling anyone. We assess what they can reach and what they can be made to do.

• Agents now act where a person used to approve

  Agents working tickets, transactions and systems move faster than manual review can follow. We put in the signals, limits and supervision that keep humans in control of what matters.

• Regulation asks for evidence you cannot produce today

  EU AI Act obligations, NIST AI RMF alignment, an internal AI policy engineering can actually follow. We translate the requirements into technical controls and the evidence that backs them.

• AI risk and security assessment

  Discovery, threat modelling, security testing and evaluations across your AI systems and use cases.

  You leave with: Prioritised findings and a plan your teams can execute.

  3 to 8 weeks

• Deep-tech advisory on AI security

  Architecture review, vendor and control selection, and second opinions for security, data and engineering leads.

  You leave with: Answers you can defend internally, from people who work hands-on in these systems.

  Retainer

• Governance and regulatory programme

  Allowed use, policies, risk registers and audit evidence, connected to the technical controls that back them.

  You leave with: Governance that strengthens posture instead of documenting it.

  4 to 12 weeks

• Controls, supervision and evaluations

  Findings turned into working controls: guardrails tuned to your context, supervision of agentic behaviour, and evaluation pipelines integrated into how you operate AI.

  You leave with: Controls your teams understand, test and own.

  6 to 14 weeks

Every engagement starts with a short discovery call and is scoped to what will actually reduce risk. Ask us for the investment ranges that match your setup.