AI systems built for production,
not just impressive demos
We design and ship the AI that businesses actually run on, retrieval-augmented generation grounded in your own data, tool-calling agents that automate real workflows, custom GPT and LLM integrations inside your product, and the backend to deploy it reliably.
Four AI capabilities,
one production-ready delivery.
Most AI projects stall between a working prototype and something a business can depend on. Each of these is built, tested, and deployed to run in production, with full code ownership handed to you.
RAG Systems
Retrieval-augmented generation that answers from your own documents, knowledge base, or database, with vector search, proper chunking, and citations so answers are accurate, not hallucinated.
Explore RAG SystemsAI Agents
Tool-calling agents that take actions, not just chat, connecting to your APIs, databases, and tools to automate multi-step workflows with the right guardrails and human oversight.
Explore AI AgentsCustom GPT & LLM Integration
OpenAI and Claude integrated directly into your existing product or workflow, custom assistants, content and support automation, and structured outputs your systems can actually use.
Explore LLM IntegrationAI Backend & Deployment
The production infrastructure behind the AI, scalable APIs, hosting, caching, monitoring, and cost control, so your AI features stay fast, reliable, and affordable as usage grows.
Explore AI BackendThe gap between an AI demo and an AI system is where most projects die
A prototype that works in a notebook is not a product. We build for real data, real users, and real edge cases from day one, so what we ship keeps working after launch.
Grounded, Verifiable Answers
RAG and citations mean the AI answers from your approved data, and users can verify it.
Security & Data Isolation
Deployed in your own cloud where needed, with access rules and no training on your data.
Production Performance
Latency, cost, and reliability engineered in, not bolted on after the demo impresses.
Full Code Ownership
Pipelines, prompts, and configuration are yours, no vendor lock-in, no black box.
AI Development, Frequently Asked Questions
Answers to the questions US & UK clients ask us most.
What does an AI development company actually build?
DappersTech builds production AI systems, not demos: retrieval-augmented generation (RAG) pipelines that answer from your own data, tool-calling AI agents that automate workflows, custom GPT and LLM integrations inside your existing product, and the AI backend and deployment infrastructure to run it all reliably.
Which AI models and platforms do you work with?
We work with OpenAI (GPT) and Anthropic (Claude) as primary models, alongside open-source models where self-hosting is required. On the infrastructure side we use vector databases like Pinecone and pgvector, orchestration with LangChain, and automation platforms such as n8n, Make, and Zapier.
Do we get full ownership of the AI system you build?
Yes. Full code ownership is transferred to you on every project, the pipelines, prompts, vector store configuration, and deployment. There is no vendor lock-in and no black box.
How long does an AI development project take?
A focused, production-ready AI build typically takes 3 to 6 weeks depending on data sources, integrations, and security requirements. We start with a fixed-scope build so you get a working, measurable system rather than an open-ended experiment.