Enterprise AI services, from strategy to production
Relevance Lab delivers AI consulting, generative AI development, AI agent development, LLM and RAG development, and AI integration — custom AI solutions engineered for enterprise data, security and scale.
Quick answerAI services are the consulting, engineering and managed-delivery capabilities used to design, build, integrate and operate artificial intelligence solutions. Relevance Lab delivers AI services end to end — AI strategy and consulting, generative AI and custom AI development, AI agent development, LLM and RAG development, AI integration, and dedicated AI developers — from proof of concept to production, with Responsible AI governance throughout.
AI services that connect strategy, build and run
Nine connected practice areas. Start with one, or run them together as a single enterprise AI program — each links to a dedicated services page.
Generative AI Services
Generative AI development, consulting and implementation on GPT, Claude, Gemini, Llama and Mistral — from GenAI proof of concept to production rollout.
ExploreAI Development Services
Custom AI application development and machine learning engineering — technology-agnostic builds tailored to your data and workflows.
ExploreAI Consulting Services
AI strategy, roadmap and advisory — high-value use case discovery, data and platform readiness, ROI and Responsible AI operating model.
ExploreAI Agent Development Services
Autonomous and agentic AI development — reasoning loops, tool use, multi-agent orchestration and human-in-the-loop control.
ExploreLLM Development Services
Custom large language model solutions — fine-tuning, private LLMs, LLM application development and evaluation pipelines.
ExploreAI Integration Services
Connect OpenAI, Claude and open LLMs into your CRM, ERP, data warehouse and internal APIs with secure, governed pipelines.
ExploreRAG Development Services
Retrieval-augmented generation — RAG chatbots and enterprise AI knowledge assistants grounded in your own content.
ExploreHire AI Developers
Dedicated AI, LLM, generative AI, AI agent and RAG engineers plus prompt engineers — staff augmentation or a managed AI pod.
ExploreEnterprise AI Services
Generative AI, agents and LLMs at scale — the cross-cutting practice for enterprise AI adoption, governance and operations.
ExploreThe AI capabilities we build across
From classic machine learning to generative AI, agents and RAG — one engineering team across the full AI stack.
Machine learning & deep learning
Predictive and prescriptive models, recommendation systems, forecasting and classification, built and deployed with MLOps discipline.
Generative AI & LLMs
LLM-powered applications, prompt engineering, fine-tuning, structured output and evaluation across foundation models.
Agentic AI
AI agents that plan, call tools and take multi-step actions, with orchestration, memory and guardrails for production use.
RAG & knowledge retrieval
Vector search, chunking and retrieval pipelines that ground AI answers in your documents, data and systems of record.
NLP & conversational AI
Natural language processing, chatbots, copilots and assistants for customer, employee and developer experiences.
Computer vision
Image and document understanding, classification, detection and OCR pipelines for automation and quality use cases.
MLOps & LLMOps
CI/CD for models and prompts, versioning, observability, drift and hallucination monitoring, and cost controls.
Data engineering for AI
Pipelines, feature stores and governed data products that make enterprise data usable — and trustworthy — for AI.
We build on the models that fit your use case
Model-agnostic by design. We help you choose — and stay portable — across commercial and open foundation models.
Custom GPT and OpenAI API development, ChatGPT integration, and assistant tooling.
Claude application and Anthropic API development, long-context and tool-use workloads.
Multimodal builds and integration with Google Cloud and Vertex AI.
Open-weight deployments where data residency, cost or control matter.
Efficient open models for latency- and cost-sensitive use cases.
Self-hosted and on-premise models for security- and compliance-driven enterprises.
A path from first use case to AI in production
The same delivery model whether you engage us for a single AI proof of concept or a multi-year enterprise AI program.
Assess
AI readiness, risk and ROI assessment with a prioritized 30-60-90 day roadmap.
Prototype
PoC or MVP against a real use case to prove value, feasibility and cost before scaling.
Build
Production engineering — models, agents, RAG, guardrails, evaluation and UX.
Integrate
Wire AI into your enterprise systems, identity, data and workflows.
Operate
Monitor, evaluate and optimize continuously — accuracy, safety and spend.
An AI services partner built for the enterprise
AWS-native AI delivery
Generative AI on Amazon Bedrock, model work on SageMaker, and GPU infrastructure at enterprise scale.
Platforms, not just people
RLCatalyst for AI operations and Spectra for data analytics accelerate build and run.
Strategy through to run
One partner from AI consulting and roadmap to development, integration and managed operations.
Responsible AI by default
Privacy controls, evaluation, bias and hallucination testing, audit logging and human oversight.
GenAI framework for AIOps & SRE
Field-tested accelerators for agentic automation across cloud, data and operations.
Enterprise scale
350+ Data & AI specialists and 150+ delivered projects across regulated industries.
Engage the way that fits your team
Project-based
A defined outcome — assessment, PoC, or a production AI application — delivered to a fixed scope and timeline.
Dedicated AI team
Dedicated AI, LLM and agent engineers embedded in your team through our Hire AI Developers practice.
Managed AI services
Relevance Lab owns build and operations on an ongoing basis, backed by RLCatalyst and Spectra.
- AWS
- DataStax
- Salesforce
- Snowflake
Enterprise AI solutions, tuned by industry
The same core AI services, adapted to the data, risk and compliance constraints that matter most in your 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.
Scaling AI 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 insights & case studies from Relevance Lab
How our teams apply generative AI, agents, LLMs and RAG in production — and what we’ve learned doing it.
Agentic AI vs Generative AI: key differences and enterprise use cases
Where generative AI ends and agentic AI begins — and which enterprise problems each is actually built for.
Read More BlogFrom reactive to autonomous: GenAI's role in AIOps & SRE
Moving operations from rule-based and reactive to predictive, conversational and intent-driven with GenAI.
Read More Case studyGoverned AI coding assistants with Research Gateway & Amazon Bedrock
Secure, self-service access to AI coding assistants with institutional control over data and usage cost.
Read MoreAI services: frequently asked questions
Content last reviewed: September 2026
Ready to put AI into production?
Book a working session and get an AI readiness, risk and ROI view of your top use cases — plus a 30-60-90 day roadmap.
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.