Agentic AI is software engineering + integration + controls. We build systems that are understandable to security and IT teams, with explicit tool access, permissions, evaluation, and observability.
A credible "autonomous worker" is an engineered system with five layers—not a chatbot with a fancy prompt.
Chat/task UI and review queues that give humans visibility and control over agent actions.
Agent runtime with state management, retries, timeouts, and multi-step workflow coordination.
APIs to CRM, ITSM, ERP, email, and data systems. Real integrations, not mock connectors.
Retrieval with permissions, citations, and freshness. RAG done right with access control.
Policies, approvals, audit logs, and evaluation harnesses. Governance built in, not bolted on.
Traces, metrics, and audit logs that let you understand exactly what the agent did and why.
Every production launch includes governance, security testing, and evaluation harnesses—mapped to recognized frameworks.
We explicitly address LLM-specific risks: prompt injection, insecure output handling, training data poisoning, excessive agency, and supply chain vulnerabilities.
Our governance approach aligns with NIST AI RMF concepts: risk identification, trustworthiness considerations, and lifecycle evaluation across design, development, and use.
Least privilege with separate service accounts and scoped tokens for each integration.
Required at risk points: money movement, customer comms, record deletion, policy changes.
Schemas, allowlists, and business rules that prevent unsafe or nonsensical outputs.
Inputs, retrieved context IDs, tool calls, outputs, and approvals—all logged and queryable.
Each phase has explicit acceptance criteria signed by the business owner. We don't move forward until outcomes are validated.
15-minute fit check followed by a qualification call. We assess workflow complexity, KPI availability, data access, and risk posture before committing.
Gate: KPI definition signed by business owner. We don't build until success metrics are agreed and baseline measurements are captured.
Gate: Security review against OWASP LLM Top 10 and operational readiness checklist. Run on real cases with benchmark vs baseline.
Gate: Governance mapping (NIST AI RMF + ISO 42001 style controls). SLOs met, rollback plan ready, incident playbook documented.
Monthly KPI reporting, drift detection, change log maintenance, and backlog burn-down. Continuous improvement, not one-time delivery.
We optimize for availability across client environments, security controls, pricing transparency, and portability. No platform lock-in.
Abstract model calls so you can switch providers. OpenAI, Anthropic, AWS Bedrock, Google—designed for API evolution and deprecation cycles.
Built to work with your existing stack: Microsoft 365, Salesforce, ServiceNow, AWS, Google Cloud. MCP-compatible connectors where applicable.
TypeScript/Python backends, Temporal for orchestration, Postgres for audit logs, vector stores with ACL filtering. No proprietary runtime lock-in.
Start with a discovery call to discuss your workflows and see how our methodology applies to your specific use case.
See our approach in action
Book a Discovery Call