What We Integrate

LLM / GPT Integrations into Existing Systems

We connect GPT-like models to your SaaS, internal portals, CRM, ticketing systems, and knowledge bases — with production-grade architecture.

RAG (Retrieval-Augmented Generation) with Your Data

We build AI assistants that use your internal documents and databases to answer questions accurately — with access control and traceability.

AI APIs & Microservices

We design and implement AI-powered APIs and microservices that are easy to consume by your apps and teams — with clear SLAs and monitoring.

Automation Workflows

We integrate AI into workflow engines and automation pipelines: summarization, classification, extraction, routing, and response generation.

Security & Reliability by Design

• Access control: role-based permissions, token scoping, environment separation.
• Secrets management: secure handling of API keys and credentials.
• Auditability: logging, traceability, and visibility into AI usage.
• Production readiness: error handling, retries, fallback logic, rate-limit protection.

Common Use Cases

• Internal Knowledge Assistant: “Ask your docs” chatbot for employees (policies, runbooks, onboarding, product docs).
• Customer Support Automation: ticket summarization, suggested replies, auto-triage, chatbot escalation.
• Sales Enablement: proposal generation, account research summaries, call-note automation.
• Ops Automation: log summarization, incident reports, smart runbooks, alert enrichment.

How We Work

Integration Assessment (1 Week)

We review your systems, data sources, and requirements. Deliverable: integration design and a prioritized implementation plan.

Implementation Sprint (2–5 Weeks)

We implement the integration, validate performance and security, and deliver a production-ready solution.

Ongoing Integration Retainer

Continuous improvements, monitoring, cost tuning, reliability enhancements, and new integration features.