AI Agent Development Services We Offer in London
London agent clients do not want a demo with a happy-path video. The local bar is set by HSBC, Barclays, and NatWest deploying agents that have to survive FCA supervision; by Faculty AI and Quantexa building intelligence agents the National Crime Agency and HMRC can audit; and by Magic Circle firms running contract agents that cannot leak a single privileged document. Our services match that ceiling. We build customer-facing agents under FCA Consumer Duty with calibrated handoff to human advisors, vulnerable-customer detection, and outcomes telemetry that feeds the board pack. We build internal operations agents (KYC, AML, claims triage, complaints handling, contract review) with full audit trails, deterministic action gates, and reversible-action design. We build clinical workflow agents for NHS Trusts under DCB 0129 and 0160 with a clinical safety officer review and a hazard log. Every engagement ships with an Article 22 analysis, an FCA Consumer Duty impact assessment where applicable, and an agent risk register modelled on the joint Bank of England, PRA, and FCA AI feedback statement.
Our AI Agent Development Development Process
We run discovery, design, build, and rollout on UK working hours so London CTOs, model risk officers, DPOs, and clinical safety officers get synchronous standups. Discovery opens with an agent autonomy tiering workshop adapted from the FCA's AI discussion paper DP5/22 and the AI Safety Institute's published evaluations: pure-advisory agents (output reviewed by a human before action), gated-action agents (agent proposes, human approves specific actions), constrained-action agents (agent acts within a deterministic policy envelope), and autonomous agents (rare, only for low-stakes reversible actions). Most regulated London deployments live in tiers one through three. Build sprints are two weeks, reviewed against an evaluation harness covering task accuracy, tool-use safety, prompt injection resistance, jailbreak resistance, PII leakage, demographic fairness under the Equality Act 2010, and reversibility of every action the agent can take. Rollout is shadow mode first, then a measured ramp with kill switches and documented rollback that internal audit, the FCA, the PRA, the SRA, or NHS clinical governance can sign off without a separate review.
Process Discovery
1-2 WeeksWe sit with the people doing the work in {city} and record the real process — including the exceptions they handle by instinct, which are exactly what kill naive automations.
Tool Surface Design
1-2 WeeksEvery system the agent touches gets a typed, permission-scoped tool with its own rate limit and rollback path. The agent gets a narrow set of verbs, never raw admin access.
Build & Evaluate
3-6 WeeksThe agent is built alongside its evaluation suite from day one, using real tasks from your business with verified outcomes. Every change is scored before it ships.
Shadow Mode
2-3 WeeksThe agent runs against live traffic but commits nothing. We compare its proposed actions to what your team actually did and tune until agreement is high enough to trust.
Staged Autonomy & Run
OngoingAutonomy is released by risk band — reversible actions first, irreversible ones keeping a permanent human gate. Then we monitor completion rate, escalations, latency and spend.
Technologies We Use for AI Agent Development
London agent workloads almost always demand UK residency, sovereign keys, deterministic action gates, and forensic audit trails. We default to AWS eu-west-2 (London), Azure UK South (London), and GCP europe-west2 (London) for orchestration, inference, and audit logs. Agent orchestration runs on LangGraph, CrewAI, AutoGen, or custom state machines depending on complexity, with deterministic tool registries, schema-validated tool inputs and outputs, and explicit policy envelopes for every action. For reasoning we use Claude via Bedrock eu-west-2 with cross-region disabled, Azure OpenAI in UK South under Microsoft Cloud for Sovereignty, Gemini 2.5 via Vertex europe-west2, and self-hosted Llama 3 70B, Mistral Large, or Command R+ on London GPU instances for full weight sovereignty. Evaluation uses Inspect AI (the UK AI Safety Institute's open-source framework), Promptfoo, DeepEval, and custom red-team suites tuned to OWASP LLM Top 10 and the AI Safety Institute's published evaluation patterns. Every tool call is logged with full inputs, outputs, and a cryptographic chain so audit can reconstruct any agent decision.
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