Generative AI Development Services
Generative AI that actually ships to production. We design, build, and deploy enterprise generative AI applications on your data, in your cloud or on your premises, grounded in the retrieval and data engineering that makes answers accurate.
As a generative AI development company built on 15+ years of search and data engineering, we cover the full lifecycle: use-case discovery, RAG and retrieval, LLM integration and fine-tuning, agents, evaluation, and production hardening. Delivery runs through our fixed-path AI Launchpad program and typically reaches production within weeks.
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Featured Case Studies
A generative AI system over Max Security's proprietary intelligence: SCOUT AI combines OpenSearch retrieval with AWS Bedrock and Anthropic Claude so analysts get grounded, sourced answers in seconds, cutting briefing time by 79%.
A hybrid retrieval framework on Elastic Cloud with AWS Bedrock, Nova, and Cohere V4 that lifted search precision and sharply reduced failed searches. It is the retrieval backbone for ScreenSteps' AI answers.
The Challenge
Most generative AI initiatives stall somewhere between the demo and the product. In our experience the model is rarely what fails. Projects get stuck on retrieval quality, data pipelines, hallucination control, evaluation, security, and cost per query. All of these are data and systems engineering problems.
This is engineering we have been doing for years. We came to generative AI from search and data infrastructure (Elasticsearch, OpenSearch, ClickHouse, Databricks), and it shows in what we ship: systems grounded in your data, with retrieval and pipelines that hold up in production.
Custom Generative AI Development Services
Every GenAI development engagement is built around your data, your stack, and your use case, end to end:
RAG Development & Semantic Search
Retrieval-Augmented Generation pipelines with hybrid vector and keyword search, chunking, reranking, and context assembly. Grounded, accurate answers over your documents, built on the search infrastructure we know best.
LLM Integration & Fine-Tuning
Model selection, prompt and context engineering, fine-tuning, and private or local deployment on AWS Bedrock, Anthropic Claude, OpenAI, and open-source models. See our LLM development services for the full track.
AI Agents & Agentic Workflows
Agents that reason, call tools, and act on your systems, with orchestration, guardrails, evaluation, and observability included. See our dedicated AI agent development services.
Generative AI Integration Services
Generative AI integration into your existing products, data platforms, and workflows: APIs, streaming pipelines, security, compliance, and the evaluation and cost controls that keep it running in production. The same team covers generative AI software development end to end, from the data layer to application code.
Why Choose Us as Your Generative AI Development Company
Grounded in Your Data
Generative AI is only as good as the retrieval and data behind it. Our search and data engineering roots mean the RAG pipelines, indexes, and data quality underneath your AI get engineered properly from the start, rather than patched in after the demo.
A Fixed Path to Production
Every project runs our Launch Sequence: use-case fit, build on your real data, harden with evals, guardrails, and cost controls, then launch and operate. You get to production in weeks, with measurable accuracy, latency, and cost-per-query targets.
Vendor-Neutral, Your Cloud
We recommend the models, clouds, and tools that fit your requirements and budget, whether commercial or open source, and everything we build runs in your cloud or on-premises. Your data never has to leave your environment.
Frequently Asked Questions
What do generative AI development services include?
Generative AI development services cover the full path from use case to production system: data pipelines and indexing, retrieval and RAG development, LLM integration, agent orchestration, evaluation and guardrails, and cost and latency tuning. Everything is delivered on your data, in your cloud or on-premises.
What is RAG as a Service?
RAG as a Service means we build and operate your retrieval-augmented generation stack for you: ingestion, hybrid vector and keyword search, context assembly, and the LLM layer. You get grounded answers over your documents without hiring a search engineering team.
How much do generative AI development services cost?
It depends on scope. A focused RAG or LLM proof of concept typically starts in the tens of thousands of dollars, while a production system with retrieval, integrations, evaluation, and hardening is a larger engagement. After a short discovery phase we give you a fixed plan and budget scoped around measurable outcomes: accuracy, latency, and cost per query.
Do we need generative AI development or generative AI consulting?
Consulting answers the what and the whether: use-case discovery, feasibility, architecture reviews, and an AI roadmap (see our generative AI consulting services). Development is the build itself, where we design, implement, and ship the system. Most engagements start with a short consulting phase and flow straight into development.
Which models and platforms do you build on?
AWS Bedrock and SageMaker, Anthropic Claude, OpenAI, Google Gemini, and leading open-source models, with retrieval on Elasticsearch, OpenSearch, and vector databases, and data platforms like ClickHouse and Databricks. We are vendor-neutral and pick the stack that fits your requirements and budget.
What are common enterprise use cases for generative AI?
The enterprise generative AI use cases we build most often are knowledge assistants and RAG-powered search over internal documents, customer support automation, research and intelligence briefing, document processing and summarization, and agentic workflow automation. The common thread is grounding the model in company data so answers are accurate and sourced.
Ready to Ship Generative AI That Works?
Bring a use case and we'll evaluate feasibility on your actual data, then outline the path from idea to a production system you can operate.
Related AI Resources: The AI Launchpad Program · AI Agent Development Services · LLM Development Services · Generative AI Consulting · GenAI & RAG on AWS · What is RAG?
