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AI Systems Integration

We weave AI into the systems you already run.
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Our AI integration practice connects modern AI services — LLMs, vector stores, agents, ML pipelines — to the platforms, registries, banks, and partners that already run your business. We make AI usable inside real workflows: governed, traceable, and operable under enterprise SLAs.

Most organizations don't need another AI demo — they need their existing systems to talk to AI safely and at scale. We design AI integration landscapes (API gateways, event streams, RAG pipelines, agent orchestration, model gateways, MCP-style tool layers), build the connectors to legacy and modern stacks alike, and operate the runtime. We are fluent in the realities of regulated environments: data residency, PII redaction, audit trails, prompt and response logging, model risk management, and human-in-the-loop controls. The result: AI features your auditors, your CISO, and your operations team can all live with.

What you get

Concrete deliverables — no fluff.

AI integration architecture — model gateways, RAG, agents, tools
LLM / vector DB / ML service connectivity to core systems
API design, governance & developer experience
Legacy adapters (mainframe, SOAP, file, DB-level) for AI workflows
Identity federation, SSO, OAuth2 / OIDC, scoped AI access
Prompt/response logging, tracing, evaluation & SLA-grade observability

Outcomes we've already delivered.

AI capabilities shipped inside regulated banking and public-sector platforms

Project: ORIZONT

Hundreds of integrations live across public registries — now AI-aware

Audit-ready prompt, response, and decision traceability end-to-end

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