Review model
Human approval remains mandatory for customer-facing or financially material actions. Low-confidence outputs route to manual review. Changes are logged to support audit and coaching.
Governance
Reviewable by design
We design workflows to be useful, reviewable, and safe in day-to-day operations. Outputs are treated as assistive recommendations unless explicitly agreed otherwise — with human gates on anything customer-facing, financial, or compliance-sensitive.
Three pillars of quality control
Review, content integrity, and measurement — applied consistently across assistants, workflow automation, and multi-agent programmes.
Content & data
No fabricated claims, relationships, or event references. Only approved data sources and agreed access boundaries. Client tone and policy constraints preserved in generated drafts.
Measurement
Every pilot tracked against baseline metrics — speed, quality, and outcome indicators. Expansion decisions made on measured performance, not volume of generated output.
What we enforce in production
Assistive, not autonomous
Agents draft, classify, and route — your team approves before anything reaches a customer, ledger, or regulator.
Evidence-linked outputs
Claims tied to retrievable sources where the domain requires it — bids, compliance packs, and customer comms included.
Fail closed on ambiguity
Low confidence or policy conflict stops the workflow and escalates — rather than guessing and hoping.
Observable by default
Structured logs for runs, tool calls, and human decisions so operations and audit can reconstruct what happened.
Human gates
Validation before action
The agent run loop includes explicit checkpoints — not bolted on after the fact. For how triggers, tools, and gates execute in practice, see How agentic workflows run.
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Trigger & classify
Event arrives from email, queue, schedule, or webhook. Intent and risk tier assigned before any outbound action.
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Draft & validate
Agent retrieves approved sources, drafts the next step, and runs validation rules against policy and confidence thresholds.
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Human sign-off
High-risk paths pause for explicit approval. Approved actions are logged; rejected paths return to manual handling.
Governance across delivery types
The same review discipline applies whether you are shipping a single assistant or a multi-workflow programme. See how we work for the engagement lifecycle.
Customer-facing assistants
Brand guardrails, escalation paths, and approval before any message leaves your environment.
Finance & operations
Exception handling, coding, and follow-up workflows with audit trails operations can defend.
Tender & bid packs
Evidence-linked drafts and human review before submission — no unsourced claims in live packs.
Compliance & SOC 2
Structured evidence collection, gap analysis, and controls suitable for security-conscious buyers.
Go deeper on governance
KPIs for AI pilots that hold up
Baseline discipline, leading vs lagging indicators, and explicit stop rules for month three reviews.
How agentic workflows run
Triggers, tools, validation layers, and human gates in the agent run loop.
What is agentic AI?
Governed workflows, chatbot distinctions, and when orchestration is the right shape.
SOC 2 readiness workflows
Evidence collection, gap analysis, and audit-friendly dashboards for SMEs.
Start here
Discuss governance for your programme
Book a consultation to map review gates, data boundaries, and measurement criteria before any build starts.
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