AI integration services.
Enterprise AI integration that ships.

AI integration services connect AI models and agents to the software your business already runs on — CRM, ERP, support tools, internal apps. We handle the discovery, design, build, and operational pieces: choosing the right model per workflow, designing the integration pattern (event-driven, API wrapping, RAG), writing the code, and running the system in production with logging, retries, and monthly cost reporting. The goal is workflows that pay back fast, not slide decks.

Three signals usually mean you're ready. (1) You have a workflow that's expensive in people-hours and includes natural-language judgment — ticket triage, document review, lead qualification. (2) Your data lives in modern SaaS with APIs (Salesforce, NetSuite, Zendesk, Slack) — we can plug into without re-platforming. (3) You have a buyer with a budget and a measurable success metric. If you've shipped two AI pilots that died at the demo stage, the missing piece is usually integration discipline, not better models.

The honest answer depends on the workflow. Typical patterns we ship: 30–60% time saved on tier-1 support, 70–90% straight-through processing on document workflows, 15–25% lead-quality improvement on enriched accounts. The compounding benefit is operational: each integrated workflow keeps running and feeding data back, which makes the next integration faster and cheaper. We report cost-of-ownership monthly so the ROI is visible, not theoretical.

All of the major ones, chosen per workflow. Anthropic Claude (best for long-context document work, tool use, agentic flows). OpenAI GPT-4 and GPT-4o (mature ecosystem, structured outputs, vision). Google Gemini (cost-competitive on high-volume classification). Meta Llama 3 and Mistral (self-hosted for compliance or cost-sensitive workloads, run on Modal, Replicate, or your own cloud). We're model-agnostic and openly evaluate the tradeoff per use case — latency, cost, quality, privacy.

Yes, and CRM is one of our most common integration targets. We work with Salesforce (REST and Bulk APIs, Apex when needed), HubSpot, Pipedrive, Microsoft Dynamics 365, Zoho, Close.io. Common patterns: AI account enrichment, lead scoring with explanations, call transcript summarization with CRM update, opportunity-stage advisor, churn-risk scoring. We never ask you to migrate CRM; we build adapters where APIs are weak.

Compliance posture is decided per project. For HIPAA, SOC 2, or regulated environments we use models with the right BAA or self-hosted (Claude Enterprise, Azure OpenAI, Llama on your VPC). All vendor calls disable training-on-your-data. We log every prompt and response with a 30-day retention default that you can shorten. We provide an architecture review and DPIA template at audit stage so your security team sees the full picture before code ships.

Three tiers. A one-week audit is $3,000 — discovery, system mapping, 90-day roadmap, ranked workflow candidates. A 30-day pilot integration is $10,000–$25,000 fixed price — one workflow shipped end-to-end against real systems. An ongoing integration team is from $5,000 per month — embedded PM and engineers shipping integrations on your roadmap with monthly cost-of-ownership reporting. Per-workflow run-cost (model calls, vector DB, monitoring) typically lands at $200–$1,500 per workflow per month depending on volume.

Most pilots ship in 30 days. The realistic distribution: simple integrations (CRM enrichment, ticket triage with RAG over a clean docset) in 2–3 weeks. Mid-complexity (multi-system agents, document processing with eval suite) in 4–6 weeks. Complex (regulated workflows, multi-model routing, custom evals against historical data) in 6–10 weeks. We don't quote a 30-day timeline for work that takes 90 days — the audit phase tells us which bucket you're in before any contract.

Enterprise AI solutions are AI features built into the systems your business already runs — not separate AI tools your team has to learn. A real enterprise AI solution looks like: a CRM with AI-enriched accounts (Claude summarizes call notes inside Salesforce), an ERP with AI invoice extraction (GPT-4 vision pulls PO data into NetSuite), a helpdesk with RAG-powered tier-1 deflection (a Claude agent drafts Zendesk replies from your docs). The buyer pattern is always the same: identify a high-judgment workflow with measurable cost, integrate AI where the data already lives, monitor cost and quality monthly. We've shipped enterprise AI integration across CRM, ERP, support, document workflows, internal copilots, and voice systems — same loop, different surface.

Yes — AI integration consulting is our standard entry point. The one-week consulting audit ($3K fixed) maps your systems, data flows, auth model, and compliance constraints, then delivers a 90-day integration roadmap with ranked workflow candidates, rough costs, and a target-stack diagram. You sign off on the architecture before any code ships. About 70% of clients move from AI integration consulting straight into a pilot build; the other 30% take the roadmap and execute in-house. Both are valid outcomes — we don't push clients into builds they're not ready for.

Four signals to filter on when picking an AI integration company. (1) Code ownership — your prompts, your repo, your data, not the vendor's. (2) Model-agnostic — they should ship Claude AND OpenAI AND open-source, and tell you which fits each workflow honestly. (3) Eval-first — they should rebuild your eval suite before touching the model, and run shadow-mode comparisons before any cutover. (4) Cost transparency — monthly $-per-integration reports, not slide decks. Most AI integration companies fail at least two of these. The audit phase is where you find out which ones; ask for a sample audit-output before you sign anything.

Yes to both. Claude integration is one of our most-shipped patterns — Sonnet 4.6 for long-context document workflows, Haiku 4.5 for high-volume classification, Opus 4.7 for hardest reasoning. See our <a href="/services/claude-development/">Claude development page</a> for the full Anthropic-specific picture. OpenAI integration covers GPT-5.4, GPT-5.4-mini, GPT-5.5, the Realtime API (voice agents), the Assistants API, and OpenAI Codex — see <a href="/services/openai-development/">our OpenAI development page</a>. We pick per workflow, integrate against your existing systems either way, and report cost-of-ownership monthly. The integration discipline is the same; the model is one variable.