--- title: "Generative AI Consulting & LLM Implementation | Agility" url: https://agilitytech.ai/generative-ai-consulting description: "Generative AI consulting: RAG pipelines, AI agents, and LLM integration with Claude Opus 4 and GPT-5, shipped to production in 3 to 8 weeks. Book a free scoping call." publisher: Agility (agilitytech.ai) --- Generative AI consulting # Generative AI consulting that ships to production Generative AI consulting from Agility covers the full stack: LLM integration, RAG knowledge systems, AI agents, and document automation. [Get a generative AI roadmap](https://agilitytech.ai/contact)[See case studies](https://agilitytech.ai/case-studies) Kickoff to live system3 to 8 wks Typical RAG system3 to 4 wks AI projects delivered200+ Post-launch monitoring90 days The short answer ## What is generative AI consulting? Generative AI consulting helps 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. Agility covers the full stack and ships production-ready systems in 3 to 8 weeks. See our [generative AI consulting cost breakdown](https://agilitytech.ai/generative-ai-consulting-cost) or read our [case studies](https://agilitytech.ai/case-studies). What an engagement includes ## From retrieval to monitoring We deploy against GPT-5, Claude Opus 4 and Llama 4 depending on your data residency requirements. A typical RAG system connects to your internal knowledge base (Confluence, SharePoint, PDFs, SQL) and returns cited, auditable answers. AI agents built with LangGraph and AutoGen handle multi-step workflows: research and draft pipelines, automated customer workflows, and data enrichment processes that replace manual analyst tasks. Document automation extracts structured data from contracts, invoices and medical records. Every engagement includes model evaluation covering hallucination rate, latency and cost per query, integration into your production stack via REST API or SDK, and 90 days of post-launch monitoring. Single-use-case deployments start at $30,000 to $60,000 with fixed-scope pricing. What an engagement includes Starting price for a single-use-case deployment, fixed scope$30,000 to $60,000 Typical time for a RAG system to go live3 to 4 weeks Post-launch monitoring90 days Models we deploy against, chosen by your data residency needsGPT-5, Claude, Llama Services ## Generative AI services From strategy to production deployment, every service is scoped for speed and measurable outcomes. ### LLM integration and custom GPT deployment Connect GPT-5, Claude Opus 4, 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) Enterprise knowledge systems that answer questions accurately from your own documents, databases, and internal knowledge bases. - Document ingestion pipelines for PDFs, Word, emails - Vector database setup: Pinecone, Weaviate, Chroma - Hybrid search (semantic plus keyword) for accuracy - Answer grounding with source citations ### AI agents and autonomous workflows Multi-step AI agents that research, reason, and execute tasks across your business systems without a human check at every step. - LangChain and 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 and 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 and 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 4, Mistral, Qwen - Domain-specific training data curation - RLHF and instruction tuning pipelines - On-premise or private cloud deployment ### Generative AI strategy and roadmapping 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 to 3 days) - Build vs. buy vs. API analysis - Data readiness and security assessment - Phased 90-day implementation roadmap Industries ## 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 and e-commerce Product description generation, customer support bots, review analysis ### Logistics Shipment status bots, route optimization commentary, compliance documentation Technology ## Technology stack We work with every major LLM platform and framework: model-agnostic and infrastructure-flexible. ### LLMs GPT-5, Claude Opus 4 and Sonnet 4, Gemini 2.5 Pro, Llama 4, Mistral ### Frameworks LangChain, LangGraph, LlamaIndex, Haystack ### Vector databases Pinecone, Weaviate, Chroma, pgvector ### Cloud Azure OpenAI, AWS Bedrock, Google Vertex AI, self-hosted RAG consulting ## RAG consulting services Retrieval-augmented generation (RAG) is how you get an LLM to answer accurately from your own data instead of guessing. As a RAG consultancy, Agility designs, builds and hardens production RAG systems so your teams get cited, auditable answers from the documents, wikis and databases you already have. ### What a RAG consultant does A RAG consultant scopes the knowledge sources, designs the ingestion and chunking strategy, chooses the embedding model and vector database, builds hybrid (semantic plus keyword) retrieval, and tunes the system so answers are grounded in citations with a measured, low hallucination rate. ### RAG implementation and architecture Our RAG implementation services cover the full architecture: document pipelines for PDFs, Word, email and SQL; Pinecone, Weaviate, Chroma or pgvector; reranking; evaluation harnesses for accuracy and latency; and deployment in your cloud, private cloud or on-premises for full data control. ### Timeline and next steps Most RAG systems go live in 3 to 4 weeks. Explore our [LLM development services](https://agilitytech.ai/llm-development-services) and [OpenAI GPT development](https://agilitytech.ai/openai-gpt-development), or [talk to a RAG consultant](https://agilitytech.ai/contact). FAQ ## Generative AI consulting: common questions Timelines, cost, data control and how RAG consulting works. [Ask us something else](https://agilitytech.ai/contact) **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 to 8 weeks with Agility. A RAG system or chatbot can go live in 3 to 4 weeks. A multi-agent workflow or fine-tuned model deployment typically takes 6 to 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. **How is generative AI consulting different from general AI consulting?+** General AI consulting covers the full spectrum: predictive models, data engineering, automation, and analytics. Generative AI consulting focuses specifically on systems built on large language models: LLM integration, RAG knowledge bases, AI agents, and document and content automation. Agility does both, but a generative AI engagement is scoped around LLMs, prompt and retrieval design, hallucination control, and token-cost optimisation rather than classical machine-learning pipelines. **What does generative AI consulting cost?+** Single-use-case generative AI deployments (a RAG chatbot, a document-automation pipeline, or one AI agent) typically start at $30,000 to $60,000 with fixed-scope pricing. Larger multi-agent or fine-tuned-model programmes run higher. We scope every project to a fixed price with milestones before build. See our generative AI consulting cost breakdown or book a free scoping call for a concrete number. **What ROI can we expect from generative AI?+** It depends on the workflow, but the pattern is consistent: generative AI removes manual, language-heavy work. Our deployments have cut document processing from days to minutes, deflected large shares of support tickets, and saved analyst hours daily. We define the target metric, handling time, deflection rate, hours saved, in the first workshop and measure against it, so ROI is tracked rather than assumed. **Which LLM should we use: GPT-5, Claude, Gemini, or an open-source model?+** There is no single best model; it depends on your task, data-residency needs, and budget. We are model-agnostic and often route between them: GPT-5 or Claude Opus 4 for the hardest reasoning, smaller or open-source models (Llama 4, Mistral, Qwen) for high-volume or on-premise work where cost and data control matter. We benchmark candidates on your actual data before committing. **Do you offer RAG consulting and RAG implementation services?+** Yes. RAG consulting is one of our most-requested services. We act as your RAG consultant end to end: connecting your documents, wikis and databases to an LLM, building the retrieval and grounding layer, and shipping a production system that returns cited, auditable answers, typically in 3 to 4 weeks. We work with Pinecone, Weaviate, Chroma and pgvector and can deploy on-premises for full data control. **What does a RAG consultant do?+** A RAG consultant designs and builds retrieval-augmented generation systems: they scope the knowledge sources, engineer the ingestion and chunking pipeline, select the embedding model and vector database, build hybrid semantic and keyword retrieval with reranking, and tune the system to minimise hallucinations while grounding every answer in a cited source. At Agility this is delivered by senior engineers and evaluated on accuracy, latency and cost before go-live. Explore more ## Related services and resources [Generative AI Consulting Cost](https://agilitytech.ai/generative-ai-consulting-cost)[AI Development Pricing](https://agilitytech.ai/ai-development-pricing)[AI Implementation Services](https://agilitytech.ai/ai-implementation-services)[AI Consulting Ahmedabad](https://agilitytech.ai/ai-consulting-company-ahmedabad)[AI Consulting India](https://agilitytech.ai/ai-consulting-india)[Hire AI Developers](https://agilitytech.ai/hire-ai-developers)[AI for Healthcare](https://agilitytech.ai/ai-consulting-healthcare)[AI for Insurance](https://agilitytech.ai/ai-consulting-insurance)[OpenAI GPT Development](https://agilitytech.ai/openai-gpt-development)[Case Studies](https://agilitytech.ai/case-studies) ## 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](https://agilitytech.ai/contact) Keep exploring ## Explore related AI services The rest of Agility's AI engineering and consulting services. ### Hire AI Developers Senior, pre-vetted ML, LLM, data and MLOps engineers. Dedicated teams or staff augmentation. [Learn more](https://agilitytech.ai/hire-ai-developers) ### Custom AI Development Bespoke AI solutions designed and built to your specification. [Learn more](https://agilitytech.ai/custom-ai-development) ### LLM Development Services Fine-tuning, RAG and private LLM deployment on your data. [Learn more](https://agilitytech.ai/llm-development-services) ### AI Consulting India Global AI delivery from our India hubs. [Learn more](https://agilitytech.ai/ai-consulting-india) ### AI Consulting Ahmedabad Local AI expertise in Ahmedabad, Gujarat. [Learn more](https://agilitytech.ai/ai-consulting-company-ahmedabad) ### AI Consulting USA AI consulting and delivery for US enterprises. [Learn more](https://agilitytech.ai/ai-consulting-company-usa) ### AI Consulting for Healthcare Clinical decision support, medical document AI, and HIPAA-compliant ML for health systems. [Learn more](https://agilitytech.ai/ai-consulting-healthcare) ### AI Consulting for Insurance Claims automation, fraud detection, and underwriting AI for P&C, life, and health insurers. [Learn more](https://agilitytech.ai/ai-consulting-insurance) ### AI Consulting for Logistics Route optimization, demand forecasting, and warehouse AI for supply chain operators. [Learn more](https://agilitytech.ai/ai-consulting-logistics)