Generative AI Development ServicesPut Large Language Models to Work in Your Product
Greatodeal helps companies turn generative AI from experiments into production features. We integrate large language models such as OpenAI GPT, Anthropic Claude, and open-source models into your products and internal tools, connect them to your data with retrieval-augmented generation (RAG), and expose your systems to AI assistants through Model Context Protocol (MCP) servers.
We handle the parts that decide whether an AI feature works in the real world: data preparation, prompt and model selection, evaluation, cost control, security, and monitoring after launch.
Generative AI Services
LLM Integration
Add summarization, drafting, classification, extraction, and AI search to your existing web or mobile product.
RAG Systems
Retrieval pipelines over your documents and databases, so AI answers are grounded in your data and cite sources.
MCP Server Development
Model Context Protocol servers that let Claude, ChatGPT, and other AI assistants securely use your tools and data.
Custom GPTs & Copilots
Purpose-built AI assistants for sales, support, legal, or operations teams, embedded in the tools they already use.
Evaluation & Cost Optimization
Test suites, model comparisons, caching, and routing that keep quality high and token costs predictable.
Generative AI Consulting
Use-case discovery, build-vs-buy guidance, and a roadmap from proof of concept to production.
Generative AI Use Cases
- AI search across company documents
- Contract and policy review assistants
- Automated proposal and report drafting
- Product description and content generation
- Meeting and call summarization
- Natural-language queries over business data
- AI features inside SaaS products
- Connecting internal tools to AI assistants via MCP
How We Deliver Generative AI Development
- 01
Discovery & Scoping
We map your workflow, systems, and goals, then agree on a clear scope, timeline, and quote.
- 02
Architecture & Security
Data access, permissions, and audit logging are designed in from the start, not added before launch.
- 03
Agile Build & Demos
Short sprints with working demos, so you see progress and steer priorities throughout the build.
- 04
Launch & Ongoing Support
Production launch, monitoring, documentation, and continued improvements after go-live.
Why Choose Greatodeal
- Building AI and custom software since 2020
- Senior engineers, direct communication, no hand-offs
- Compliance-grade security, audit logs, and access control
- You own 100% of the code and IP
- Fixed-price, milestone, or monthly engagement options
- Clients across the US, UK, Europe, and the Middle East
Technologies We Use
Industries we often build this for: Fintech, Government, Healthcare.
Generative AI Development FAQs
What is generative AI development?+
Generative AI development is building software features powered by models that create text, code, or images, such as AI assistants, document summarizers, and search tools. It includes integrating the model, connecting it to your data, and making it reliable, secure, and affordable in production.
What is RAG and why does it matter?+
Retrieval-augmented generation (RAG) lets a language model look up relevant information from your own documents or databases before answering. It makes answers more accurate, keeps them current without retraining a model, and allows the AI to cite its sources.
What is an MCP server?+
Model Context Protocol (MCP) is an open standard that lets AI assistants like Claude and ChatGPT connect to external tools and data. An MCP server exposes your systems, such as a CRM, database, or internal API, so AI assistants can use them securely with defined permissions.
Which AI models do you work with?+
We work with OpenAI GPT models, Anthropic Claude, Google Gemini, and open-source models such as Llama and Mistral, and choose based on quality, cost, latency, and data-privacy needs for each use case.
Is our data safe when using generative AI?+
We use enterprise API terms that exclude your data from model training, restrict what data each feature can access, encrypt data in transit and at rest, and can deploy on private cloud or self-hosted models when required.
Ready to Start Your Generative AI Development Project?
Tell us what you want to build or automate. We reply within 24 hours with honest advice and next steps.