A delivery platform for designing, governing, testing, observing, and safely operating AI agents in regulated workflows.
Agentek helps enterprises build AI agents, but our platform is the control layer that makes those agents safe, observable, testable, and production-ready.
Agentek Control Layer provides a structured control model for regulated AI agent delivery. It brings together workflow templates, guardrails, evals, observability, audit trails, and deployment patterns that can fit client-controlled environments.
The policies, approvals, assurance expectations, and ownership model around production AI.
Workflow templates, guardrails, evals, human review, observability, security models, audit trails, and deployment packs.
The model, orchestration, retrieval, tools, data sources, and operational systems the agent works with.
The value is the control plane above existing agent frameworks and below enterprise governance, not a replacement for either.
These are the assets Agentek standardises across delivery so each engagement starts with proven control patterns rather than a blank page.
Starting points for document intake, KYC, claims, compliance review, and operations support.
Reusable controls for refusal logic, escalation rules, data handling, and model behaviour limits.
Confidence thresholds, approval queues, exception routing, and reviewer decision capture.
Golden tasks, adversarial prompts, policy checks, regression tests, and business-risk thresholds.
Visibility across prompts, retrieval, tool calls, model outputs, reviewer actions, and failures.
Templates for identity, permissions, tenant separation, data minimisation, and sensitive-system access.
Traceable evidence for what happened, why it happened, who reviewed it, and what changed.
Deployment patterns, integration maps, control model, eval plan, and operating model for delivery.
Observability, security, guardrails, and evals are core parts of the Agentek Control Layer, giving regulated teams the evidence and operating controls needed to move beyond prototype-quality AI.
Instrument prompts, retrieval, tool calls, model outputs, human review, and downstream actions so teams can see what happened, why it happened, and where intervention is needed.
Design secure integration patterns around identity, permissions, data minimisation, tenant separation, prompt injection risk, and controlled access to sensitive systems.
Define what the AI system can do, what it must escalate, what it must refuse, and where deterministic rules or human approval override model behaviour.
Build evaluation sets for accuracy, retrieval quality, policy adherence, edge cases, and workflow completion so releases are measured against business risk rather than demo performance.
Document intake, KYC, claims, compliance review, and operational support patterns shaped around auditability and escalation.
Architecture and operating patterns that can sit inside client environments instead of forcing a black-box service model.
Evals, traces, dashboards, reviewer actions, policy boundaries, and audit trails give teams a way to improve the agent after go-live.
Agentek can help shape the workflow, design the guardrails, and define the production control model before the agent build begins.
