AI agents
Tool-using agents with explicit permissions, evidence, escalation, and human approval.
We design, build, integrate, and launch production AI software for teams whose needs cannot be met by an off-the-shelf chatbot.
Custom development is appropriate when AI must operate inside a specific workflow or data boundary.
Tool-using agents with explicit permissions, evidence, escalation, and human approval.
RAG and document intelligence with retrieval evaluation, citations, and access control.
Reliable workflows that combine deterministic rules, AI judgement, queues, retries, and audit trails.
A demonstration is not a production system.
Representative test sets, accuracy criteria, regression checks, and failure analysis.
Least-privilege access, tenant boundaries, sensitive-data handling, and action confirmation.
Monitoring, cost visibility, fallbacks, documentation, training, and accountable ownership.
Confirm users, workflow, data, integrations, and acceptance criteria.
Resolve uncertain model and interaction questions with working software.
Implement the system, integrations, controls, evaluation, and observability.
Pilot with real users, correct failure modes, train operators, and hand over.
Cost depends on integration depth, data condition, risk controls, evaluation needs, and operating requirements. We scope the system after diagnosis rather than price only by screen count or model calls.
No. We select models and infrastructure based on quality, latency, privacy, availability, and cost requirements.
Often yes. Options include supported APIs, database replicas, scheduled exports, event streams, or controlled interface automation. The safest route depends on the ERP and permitted access.
We will first clarify the workflow, evidence, data boundary, and outcome standard before recommending the next step.
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