04 · Integrate
RAG, LLMs, and AI integration for your product
AI integration is a fixed-price service that builds RAG, LLM, and AI-agent features directly into your product. Unbland Studio scopes your use case, wires up the models and data pipelines, and hands back a system you fully own — Claude and OpenAI API integration, vector search, and evals included — from $8,000 plus a support retainer.
Updated July 2, 2026
What is AI integration?
AI integration means wiring language models, retrieval, and autonomous agents into a product you already have or are building — not bolting on a generic chatbot. Unbland Studio connects your data to LLMs through RAG and vector search, builds agents that take real actions, and integrates APIs like Claude and OpenAI so the feature is fast, accurate, and owned by you rather than locked to a single vendor.
What can you build with RAG and LLMs?
Most AI integration work falls into a few repeatable patterns, and Unbland ships all of them as production features with evals — not demos — so you can measure accuracy before anything reaches your users.
- RAG & vector search — retrieval over your own documents, backed by embeddings and a vector database
- AI agents & automation — assistants that take actions, not just answer questions
- LLM integration — Claude (Anthropic) and OpenAI APIs wired into your product
- Data pipelines — clean, chunk, and sync the data your models depend on
- Fine-tuning & ML development — custom models when off-the-shelf isn't enough
How much does AI integration cost?
Unbland's AI Systems service starts at a fixed $8,000 plus a support retainer, covering an LLM or RAG integration scoped to a defined use case. Pricing is fixed per scope — there is no hourly billing — and the retainer covers ongoing monitoring, evals, and tuning after launch. Larger multi-agent or data-pipeline systems are scoped after discovery.
- AI system build — from $8,000 (fixed per scope)
- Ongoing support retainer — scoped to your system
- Larger multi-agent / pipeline systems — scoped after discovery
How long does AI integration take?
A typical AI integration runs 6–10 weeks from kickoff to a system running in production. The first days go to scoping your use case and data; a working prototype follows within the first few weeks; then Unbland hardens it, adds evals, and integrates it into your product. Simple single-model integrations land faster, while multi-agent systems and heavy data pipelines sit at the longer end.
Which LLMs and frameworks do you work with?
Unbland integrates the major LLM APIs — including Claude from Anthropic and OpenAI — and orchestrates agents and RAG pipelines with frameworks like LangChain. For retrieval, we design the embedding and vector-search layer on the vector database that fits your data and budget. You own every key, model, and line of integration code at handover, so you are never locked to a single provider.
Pricing
| Package | Price | Includes |
|---|---|---|
| AI System Build | from $8,000 |
|
| Support Retainer | Scoped |
|
Process & timeline
| Stage | What happens | Timeline |
|---|---|---|
| 1 · Scope | We map your use case, data sources, and success metrics, then decide which models, retrieval, and agents fit. | Days 1–5 |
| 2 · Prototype | We build a working proof of concept — a RAG index, agent, or API integration wired to your real data and measured with evals. | Weeks 1–3 |
| 3 · Build & integrate | We harden the system into your product with data pipelines, LLM API integration, and accuracy checks. | Weeks 3–8 |
| 4 · Handover & support | You get a 30-day handover call, 30 days of included support, full documentation you own, and an optional retainer for ongoing monitoring and tuning. | Weeks 8–10 |
By the numbers
Frequently asked questions
- Do you offer RAG development services?
- Yes. RAG (retrieval-augmented generation) is one of our core AI Systems offerings — we build retrieval over your own documents using embeddings and a vector database, then connect it to an LLM with evals to keep answers accurate. A scoped RAG integration starts at $8,000 and typically ships in 6–10 weeks.
- Are you a LangChain agency?
- We build production AI systems and orchestrate agents, tools, and RAG pipelines with frameworks like LangChain where they are the right fit. We stay framework-agnostic, picking the stack that keeps your system reliable and easy to own rather than forcing one library. Every integration is handed over with source code and documentation.
- Can you integrate the Claude API into our product?
- Yes. We integrate Anthropic's Claude API directly into your product — for chat, agents, RAG, or automation — and wire it into your existing stack and data. You keep your own API keys and all integration code at handover, and this work is part of the AI Systems service from $8,000 plus a retainer.
- Do you do OpenAI API integration?
- Yes. We integrate OpenAI's APIs for LLM features, embeddings, and vector search, and we can run Claude and OpenAI side by side so you are not locked to one provider. Integrations are fixed-price from $8,000 and usually ship within 6–10 weeks.
- Can you act as a vector search consultant?
- Yes. We design the embedding and vector-search layer end to end — choosing the vector database, chunking and indexing your data, and tuning retrieval quality with evals. It can be scoped as a standalone piece or as part of a full RAG build starting at $8,000.