AI Integration
Add AI to the product you already have.
Search, extraction, summaries and assistants built into your current app and data. No platform switch.
Input
Hi, this is Priya from Northwind. Please send 40 units of SKU A-220 to our Pune warehouse by 12 March. PO number is 88341.
Output
{
"customer": "Northwind",
"sku": "A-220",
"quantity": 40,
"ship_to": "Pune warehouse",
"due": "2026-03-12",
"po": "88341"
}Emails, PDFs and forms become clean records in your system.
How AI answers from your own data
This is retrieval-augmented generation (RAG). The model does not guess from its training. It reads your content first, then answers and shows where it found it.
Your content
Docs, tickets, PDFs, Notion, Drive or your database.
Index
Split into passages and stored in a vector database.
Retrieve
Each question pulls the most relevant passages.
Answer
The model answers from those passages and cites them.
The right model for each job
We are not tied to one provider. Features are built so you can switch models as prices and quality change.
OpenAI GPT
General reasoning, structured output and voice.
Anthropic Claude
Long documents, careful writing and tool use.
Google Gemini
Large context, images and video input.
Open-source models
Llama or Mistral hosted on your own servers when data cannot leave.
Start small, prove it, then roll out
Prototype
One use case, working on a sample of your real data.
Evaluate
Your team tests it on real cases. We measure accuracy and fix gaps.
Roll out
Production release with monitoring, cost tracking and feedback.
Your data stays your data
Keys stay on the server
The browser never sees your AI provider keys.
No training on your data
We use API tiers where providers do not train on inputs.
Permission-aware answers
Users only get answers from content they are allowed to see.
Self-hosting option
Open-source models on your infrastructure for strict compliance.
Questions about adding AI
Not covered here? Email hello@eqvilabs.com.
Can you add AI to my existing app?
Yes. We integrate LLM features into your current codebase through your backend, so API keys and data stay under your control.
What is RAG?
Retrieval-augmented generation. The AI searches your own documents or database first, then answers from that content, which makes responses accurate and specific to your business.
Is my data used to train AI models?
No. We use API tiers where providers do not train on your data, and we can host open-source models on your own infrastructure when required.
How long does it take to add an AI feature?
A working prototype on your data usually takes one to two weeks. Production rollout follows once your team has tested it on real cases.
How much do AI features cost to run?
It depends on usage and model choice. We estimate cost per request during the prototype and add caching and model routing to keep it low.