AI Integration Services

    Add AI to what already works without rebuilding.

    AISD integrates AI into your existing products and workflows. Not a rip-and-replace. Not a 6-month R&D project. A production integration that ships in 4-8 weeks and generates ROI from day one.

    $25K+ fixed-price integrations · 4-8 wk to production · Eval harness included

    Integration patterns

    Four patterns. Pick the one that fits.

    01

    API-first AI embedding

    Connect frontier models (GPT-5, Claude, Gemini) into your existing product via clean API layers. Structured prompts, retry logic, fallback chains, and cost controls from day one.

    Use case: SaaS products adding AI features, internal tools augmenting with intelligence

    02

    RAG pipelines

    Retrieval-augmented generation over your proprietary data. Document ingestion, vector indexing, hybrid search, and grounded generation with citation tracking.

    Use case: Knowledge bases, customer support, legal document search, internal wikis

    03

    Model orchestration

    Multi-model routing where different tasks hit different models based on cost, latency, and accuracy requirements. A/B testing between models with eval-driven promotion.

    Use case: High-volume pipelines, mixed workload products, cost-sensitive deployments

    04

    Workflow automation with AI steps

    n8n, Zapier, or custom workflows with AI decision nodes: classification, extraction, summarization, and routing integrated into your existing business processes.

    Use case: Operations automation, document processing, lead qualification, support triage

    Tech stack

    We integrate with the tools that matter.

    OpenAI GPT-5 / GPT-5-miniAnthropic Claude 4Google Gemini 2.5LangChain / LangGraphPinecone / Weaviate / Qdrantn8n / Zapier / MakePydantic AIAWS / GCP / Azure

    What you get

    Every integration ships with these.

    • Eval harness. Automated test suite that measures accuracy, latency, and cost before and after deployment. Runs in CI.
    • Observability. Structured logging, cost tracking per model call, drift detection, and alerting. You see what the AI is doing.
    • Security review. Prompt injection testing, PII detection, rate limiting, and audit logging. Baked in, not bolted on.
    • Handoff runbook. Documentation, architecture diagrams, on-call procedures, and a 30-day post-launch support window.

    Next step

    Scope your AI integration in 30 minutes.

    Tell us what you're building and what systems need AI. We'll tell you which pattern fits and what it costs.