System Integration
The model works in a notebook. It cannot access production data or trigger downstream workflows. Integration is where most AI projects stall. We wire models into your systems so they run as infrastructure, not sidecar experiments.
A model that cannot reach production data or push results into the systems people use daily is a demo. Not a deployment.
AI systems consume unstructured data and produce probabilistic outputs. Enterprise platforms expect structured inputs, deterministic behavior, and clean error handling. Bridging that gap requires specific engineering: REST and event-driven APIs connecting model inference to business workflows, data synchronization keeping training data fresh, webhook triggers invoking models when business events occur, and error handling that manages low-confidence results gracefully instead of failing silently.
We have integrated AI models with Salesforce, SAP, Workday, ServiceNow, Snowflake, BigQuery, legacy SQL databases, and dozens of custom platforms. Each one has its own challenges. Salesforce has API rate limits that require batching strategies. Legacy systems often lack APIs entirely and require database-level integration or screen scraping as a bridge. Real-time inference endpoints need different latency management than batch pipelines. Each integration ships with monitoring, retry logic, circuit breakers, and documentation detailed enough that your internal team can maintain and extend it without calling us.
Security is built into the wiring, not bolted on after. A model that can read from Salesforce and write to your ERP holds real power, so it gets scoped credentials, least-privilege access, and an audit trail for every action it takes. Sensitive fields are masked before they ever reach an inference endpoint. The integration can do exactly what the workflow needs and nothing past it, which is what keeps a useful connection from becoming the next breach in the post-mortem.
The test is simple: six months after we leave, does the integration run like it was always there? If it requires ongoing babysitting, we did not do our job.
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