Connect AI into your enterprise stack
Enterprise AI integration services — connect models, LLMs and AI applications into your CRM, ERP, data warehouse, ticketing and internal APIs, with secure connectors, retrieval pipelines, identity and event triggers.
Quick answerAI integration services connect AI — models, LLMs and AI applications — into the systems your business already runs: CRMs, ERPs, data warehouses, ticketing, knowledge bases and internal APIs. This cluster owns all ‘integration’ intent — OpenAI, Claude and open LLMs — so connect work is not split across separate clusters.
One integration layer, three focused services
Each links to a dedicated page.
OpenAI & ChatGPT Integration Services
ChatGPT API integration into Salesforce, ServiceNow, Microsoft 365, data warehouses and internal apps.
ExploreClaude & Anthropic Integration Services
Claude API integration with tool use, retrieval and identity, via Anthropic, Bedrock or Vertex AI.
ExploreLLM Integration Services
A provider-agnostic LLM gateway with routing, fallback, caching, policy and cost controls.
ExploreRetrieval to systems of record
Permission-aware pipelines that ground AI in live enterprise data, with citations.
ExploreEvent-driven automation
Trigger AI on business events and push results back into the systems people use.
ExploreEnterprise AI Services
The integration layer as part of a full enterprise AI platform and operating model.
ExploreA reusable layer, not another point integration
Governed connectors
Least-privilege service credentials, your identity provider, and audit logging on every call.
Shared retrieval service
One place to ground any AI use case in systems of record, with per-user access filtering.
Policy & permissioning
Data-scope filtering so the AI only sees what the requesting user may see; PII redaction where needed.
Event triggers
Kick off AI on record changes, tickets or messages, and write results back automatically.
Observability & cost
Per-team usage, latency and spend, so each new use case plugs in rather than re-integrating.
Security review built in
Threat modelling, data classification and sign-off as part of delivery.
Integration or development — which do you need?
| You want to… | AI Integration (this cluster) | Development |
|---|---|---|
| Connect a model or app to enterprise data | Yes | — |
| Build a reusable connector / retrieval layer | Yes | — |
| Create a new assistant, agent or model | — | Yes |
| Design RAG, tools and evaluation | — | Yes |
| Both, on one program | Common | Common |
Integration that scales with your AI programme
Platform breadth
Salesforce, ServiceNow, SAP, Microsoft 365, Snowflake, Databricks, Jira, Zendesk and custom APIs.
Security-first
Least privilege, per-request authorisation, redaction and full audit logging.
Reusable by design
A governed layer so each new AI use case plugs in, not re-integrates.
Platforms behind the team
RLCatalyst and Spectra accelerate build and run.
Cost visibility
Per-team quotas and cost-per-use reporting on every AI call.
Enterprise scale
350+ Data & AI specialists across regulated industries.
AI integration, tuned by industry
The systems, data-sensitivity and audit requirements that shape an integration differ by sector.
Financial services
Document AI, risk and fraud models, and governed copilots that meet audit and compliance needs.
Healthcare & life sciences
Clinical and research assistants, knowledge retrieval and automation with data governance built in.
Retail & consumer
Personalization, demand forecasting, and customer and associate assistants across channels.
Manufacturing & supply chain
Predictive maintenance, quality vision, and agentic workflows for planning and operations.
Public sector
Secure, private-LLM deployments for citizen services, case work and knowledge access.
Technology & ISVs
Embed generative AI features, agents and RAG into your product with a partner who ships.
- AWS
- DataStax
- Salesforce
- Snowflake
Scaling this across the enterprise?
Our Enterprise AI Services practice brings generative AI, agents and LLMs to production at scale — with the governance, platform and operating model to keep them reliable, compliant and cost-controlled.
AI integration insights from Relevance Lab
Governed AI coding assistants with Research Gateway & Amazon Bedrock
Secure, self-service access to AI coding assistants with institutional control over data and usage cost.
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Read MoreAI Integration Services: frequently asked questions
Content last reviewed: September 2026
Need AI acting on your real business data?
Tell us the systems and the use case and we will design a secure, reusable integration layer.
Talk to an AI specialist
Tell us where you are on your AI journey — a use case, a proof of concept, or a platform decision — and an AI consultant will come back with next steps and a rough shape for the engagement.