From Prompts to Systems
We turn prototypes into production-grade AI Agents: multi-step workflows with tool-use, memory, and policy guardrails. The goal is reliable outcomes, not just responses.
Architecture
- Orchestration Graphs: Task decomposition, planner-executor loops, and routing based on context and risk.
- Tools & Skills: Connectors to REST/GraphQL, DBs, search, RAG, e‑mail, ticketing, and internal APIs.
- Memory & Knowledge: Structured short/long‑term memory and vector search for grounding.
- Observability: Traces, metrics, cost/time budgets, and A/B evaluation for continuous tuning.
Safety & Governance
Guardrails at each step: input/output validation, PII redaction, policy checks, rate‑limits, and human‑in‑the‑loop for high‑risk actions.
Integration & Deployment
Event‑driven microservices, queues and retries, containerized on Azure/AWS with CI/CD. Single‑tenant or multi‑tenant, SSO, and role‑based access for enterprise contexts.
Use Cases
- Support Copilot: Triage + action execution across CRM/ITSM.
- Ops Automation: Incident response, runbooks, and SLA‑aware remediation.
- Sales & Backoffice: Proposal drafting, enrichment, and workflow hand‑offs.
Engagement
Discovery workshop → pilot → production hardening. Clear KPIs (success rate, latency, cost per task) and safety scorecards.