Agentic AI that behaves in production.
Multi-agent systems on RapidAI: planner, researcher, coder, auditor patterns with shared memory, hard guardrails, and human-in-the-loop checkpoints. Built for chains that have to behave under audit, not just under demo.
Capabilities under one accountable team.
Agent design & orchestration
Coordinator + sub-agent patterns with shared memory, supervised handoff, retries, conditional branches, and abort-on-policy. Built for production traffic.
Tool use & enterprise context
120+ first-party connectors (Salesforce, ServiceNow, SAP, Workday, Snowflake, Microsoft 365). Tools surfaced to agents through a typed, audited registry.
Guardrails & evaluation
Content firewalls, prompt-injection defence, PII redaction, output-policy enforcement. Continuous evaluation against ground-truth and red-team prompts.
Observability & cost control
Per-agent traces, token telemetry, drift detection, cost analytics. Replayable runs for regulatory review.
Outcomes you can hold us to — by horizon.
Foundations
Outcome tree, baseline metrics, and a working pilot in production by day 90 — defensible with finance, signed off by risk.
Scale
Squad expansion across the next 2–3 value pools. Live-parallel cutovers. Capability uplift inside the client team.
Run & optimise
Managed run with named SLOs, quarterly value reviews, and a continuous-improvement budget reserved for innovation, not toil.
Five steps. One accountable team.
Use-case shape
Agent vs. workflow vs. RAG decision. ROI × feasibility × risk scoring before we build.
Design
Agent topology, tool surface, prompt strategy, evaluation harness, kill-switch design.
Build & evaluate
Sandbox-first build with synthetic data, evaluation suite, red-team review.
Promote
Model card, MRM sign-off, kill-switch test, staged rollout to a controlled tenant.
Scale
Reuse patterns, expand tool surface, FinOps the inference bill.
Tier-1 sovereign bank deploys a 4-agent loan-decisioning team — 9 days to 14 minutes, regulator pass first time.
More programmes we have shipped.
AI underwriting
9 days → 14 minGCC sovereign bank deploys AI underwriting in 11 months
Read case studyLoan origination
14d → 3hNational bank ships modern Loan Origination System on Mendix in 11 months
Read case studyOpen banking
240+ TPPsLeading African bank ships open-banking rails across 7 markets
Read case studyThree commercial models. One outcome standard.
We avoid open-ended retainers. Every model names its outcome and its measurement window in the contract.
Fixed-price diagnostic
2–4 week engagement. Outcome tree, baseline metrics, prioritised value pools, and a board-ready 18-month roadmap. Stop-go decision in week 4.
Outcome-linked pilot
8–12 week engagement to ship one value pool, end-to-end, with a measurable KPI commitment. Joint squads with the client team. Live-parallel before cutover.
Programme + managed run
Multi-quarter scale-out with managed services on top. Quarterly value reviews. SLO-tied annual incentive. Capability transfer by design.
Frequently asked questions
Are you saying agents are always the right answer? +
No. For deterministic workflows we recommend RPA + Mendix. For retrieval-grounded Q&A, plain RAG. Agents earn their place when planning, tool use, and reflection are the differentiator.
How do you stop runaway agents? +
Hard step limits, budget caps, abort-on-policy, kill-switch, and a human-in-the-loop checkpoint before destructive actions. Tested every release.
Which LLMs do you support? +
OpenAI, Anthropic, Google (Vertex), AWS Bedrock, Meta Llama (self-hosted), Mistral, Cohere, Ollama, and selected sovereign providers. Routed via RapidAI’s LLM Mesh.
How do you handle prompt injection? +
A content firewall sits in the request path with detection rules for prompt injection, jailbreak patterns, and tool-call manipulation. Every block is logged and replayable.
Audit and model risk? +
SR 11-7 aligned model cards, evaluation evidence, kill-switch tests, and change records — generated by the platform per agent, per release.
Do agents share memory? +
Through a tenant-isolated retrieval layer with per-agent scopes, citation enforcement, and right-to-be-forgotten. No cross-tenant memory ever.
Book a agentic ai briefing.
A senior partner will respond within one business day with a tailored agenda.