Chatbots and assistants
Assistants that answer from your own documents and data, with clear limits on what they can say and do.
Hire AI developers for LLM integration
TintSol's AI developers add LLM features to real products: assistants, document search, extraction, and workflow automation. We work with OpenAI and Anthropic models, Python, and retrieval tools, and test the output before it reaches users.
What our engineers build
Work you can hand to this team.
Retrieval and document search
Search over contracts, manuals, or tickets using embeddings in Pinecone, built with LangChain or LlamaIndex.
Data extraction from documents
Pulling structured fields out of invoices, forms, and emails and sending them into the systems that need them.
AI automation of workflows
LLM steps added to existing processes, such as triage, drafting, or classification, with a person approving where it matters.
Evaluation and monitoring
Test sets and checks that measure answer quality, cost, and response time before and after each change.
The stack around it
- OpenAI
- Anthropic
- Python
- LangChain
- LlamaIndex
- Pinecone
- Vertex AI
- PyTorch
- PostgreSQL
Technologies
Technologies we work with.
The core tools this team works in every day, alongside the wider stack listed above.
AI & LLM integration
- OpenAI
- Anthropic
- Python
How hiring works
From brief to a working team.
- 01
Send a brief
Tell us what you are building, what already exists, and where you need AI engineers. We reply within one business day with questions or a call slot.
- 02
Get a team proposal
We propose the people and roles the work needs, and whether a fixed-scope project with milestones or an ongoing retainer fits better.
- 03
Onboard
The team gets access to your repositories, tools, and environments, reads the existing code, and agrees working hours, channels, and a definition of done with you.
- 04
Ship on a set cadence
Work runs in short cycles with a planning session, regular demos, and written status updates, so you always know what shipped and what is next.
FAQ
Questions we hear first.
Which AI models do you work with?
Mainly OpenAI and Anthropic models, plus Vertex AI on Google Cloud. We choose per task based on quality, cost, and where your data is allowed to go, and design the integration so the model can be swapped later.
How do you keep a chatbot from giving wrong answers?
We ground answers in your own content through retrieval, limit what the assistant is allowed to do, and run a test set of real questions before each release. Where a wrong answer is costly, a person reviews the output first.
Can you add AI to an existing product?
Yes. We integrate with your current backend and data rather than building a separate system next to it.
How quickly can a team start?
Most engagements start within 5–7 business days of the initial brief. We reply to every enquiry within one business day, and the start date depends mainly on how quickly scope and the contract are agreed.
Who owns the code?
Code ownership is agreed in the contract before work starts. The code lives in repositories you can access from the first day, so you can see every commit as it lands.
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