Generative AI Consulting

Generative AI Consulting
That Ships to Production

We build LLM integrations, RAG knowledge systems, AI agents, and document automation that work in your environment not just in demos. Production-ready in 3-8 weeks.

3-8 Weeks
To Production
From kickoff to live generative AI system
200+
AI Projects
Including LLM and generative AI deployments
60-80%
Faster
Than traditional consulting firms
99%
Satisfaction
Across all generative AI engagements

Generative AI Services

From strategy to production deployment every service is scoped for speed and measurable outcomes.

LLM Integration & Custom GPT Deployment

Connect GPT-4, Claude, Gemini, or LLaMA to your internal systems with proper guardrails, cost controls, and business logic.

  • Custom GPT wrappers fine-tuned on your data
  • Secure internal API integration with access controls
  • Cost optimization: batching, caching, model routing
  • Latency benchmarking and production hardening

RAG Systems (Retrieval-Augmented Generation)

Build enterprise knowledge systems that answer questions from your own documents, databases, and internal knowledge bases accurately.

  • Document ingestion pipelines for PDFs, Word, emails
  • Vector database setup: Pinecone, Weaviate, Chroma
  • Hybrid search (semantic + keyword) for accuracy
  • Answer grounding with source citations

AI Agents & Autonomous Workflows

Deploy multi-step AI agents that can research, reason, and execute tasks across your business systems without human-in-the-loop for each step.

  • LangChain / LangGraph agent architecture
  • Tool-calling agents connected to APIs and databases
  • Agentic workflows for research, triage, and reporting
  • Human-in-the-loop checkpoints for high-stakes decisions

Document Intelligence & Content Automation

Automate document-heavy processes: contracts, invoices, medical records, compliance reports, and customer communications.

  • Structured data extraction from unstructured documents
  • Automated report and summary generation
  • Contract review and clause extraction
  • Multi-language document processing

Fine-Tuning & Domain-Specific Models

When general models fall short, we fine-tune open-source LLMs on your domain data for higher accuracy, lower cost, and full data control.

  • Fine-tuning on Llama 3, Mistral, Phi-3
  • Domain-specific training data curation
  • RLHF and instruction tuning pipelines
  • On-premise or private cloud deployment

Generative AI Strategy & Roadmapping

Not sure where to start? We map your business processes to generative AI use cases, rank them by ROI, and build a phased implementation plan.

  • Use case discovery workshop (2-3 days)
  • Build vs. buy vs. API analysis
  • Data readiness and security assessment
  • Phased 90-day implementation roadmap

Generative AI by Industry

Concrete use cases we've shipped not whitepaper concepts.

Healthcare

Clinical note summarization, prior auth drafting, patient Q&A bots

Insurance

Claims triage, policy Q&A, underwriting document extraction

Manufacturing

Maintenance report generation, quality defect analysis, supplier RFQ drafting

Finance

Financial report summarization, regulatory filing assistance, client email drafting

Retail & E-commerce

Product description generation, customer support bots, review analysis

Logistics

Shipment status bots, route optimization commentary, compliance documentation

Technology Stack

We work with every major LLM platform and framework model-agnostic, infrastructure-flexible.

LLMs
  • GPT-4o / GPT-4
  • Claude 3.5 Sonnet
  • Gemini Pro
  • Llama 3
  • Mistral
Frameworks
  • LangChain
  • LangGraph
  • LlamaIndex
  • Haystack
Vector Databases
  • Pinecone
  • Weaviate
  • Chroma
  • pgvector
Cloud
  • Azure OpenAI
  • AWS Bedrock
  • Google Vertex AI
  • Self-hosted

Generative AI Consulting Common Questions

What is generative AI consulting?

Generative AI consulting is the process of helping businesses identify, design, and implement generative AI systems such as LLM-powered chatbots, RAG knowledge bases, AI agents, and document automation tools in a way that delivers measurable business value.

How long does a generative AI implementation take?

A focused generative AI project typically takes 3-8 weeks with Agility. A RAG system or chatbot can go live in 3-4 weeks. A multi-agent workflow or fine-tuned model deployment typically takes 6-10 weeks. We scope tightly and ship fast.

Do you work with proprietary/confidential data?

Yes. We have extensive experience building systems that keep sensitive data inside your own cloud environment, never sending it to third-party model APIs. We support Azure OpenAI, AWS Bedrock, and self-hosted open-source models for full data sovereignty.

What industries do you serve for generative AI?

Healthcare, insurance, manufacturing, finance, retail, and logistics are our primary verticals. Each has specific compliance and data requirements that we handle as part of the implementation.

Ready to Ship Generative AI to Production?

Tell us your use case. We'll scope a plan and give you a timeline in 48 hours.

Talk to a Generative AI Consultant