Chat assistants
An assistant inside your app that answers from your product's data, with responses streamed as they are written.
AI Integration
AI Integration Servicesfor Mobile Apps and SaaS Products
RafayLabs adds AI features to new and existing products: chat assistants, image recognition, generated content and search over your own data, using OpenAI and Google Gemini models.
- Models we build with
- OpenAI · Gemini
- Models we build with
- Answers appear as they are written
- Streaming
- Answers appear as they are written
- Answers drawn from your own content
- Your data
- Answers drawn from your own content
- React Native and Next.js
- App + web
- React Native and Next.js
What you get
Most useful AI features are one of these. Each is a feature inside your product, not a separate chatbot.
Image recognition
Turn a photo into structured data. Recipe Lens identifies food from a fridge photo with Clarifai, then writes recipes with GPT-4.
Generated content
Text written for each user, such as the personalised horoscopes in Celestium.
Search over your documents
Retrieval-augmented generation (RAG) with vector embeddings, so answers come from your content and not from the model's guesses.
Agent workflows
Multi-step tasks the model carries out using your own tools and APIs.
Cost and usage controls
Usage metering and per-user limits, with Stripe billing when you charge for AI usage.
How it works
- 01
Pick the use case
One feature where AI saves your users time, and a way to tell whether it works.
- 02
Prototype
A working version on your real data, so you can judge the answers before it is built in.
- 03
Build it in
The feature inside your app or SaaS, with streaming, error handling and usage limits.
- 04
Measure and adjust
Review real usage and cost, then tune the prompts and the choice of model.
Related work
Apps with AI features the founder has built, and in what role.
Recipe Lens
Recipes from a fridge photo, with Clarifai and GPT-4
Freelance client project
See in portfolio
Questions
Which AI models do you work with?
OpenAI models such as GPT-4, Google Gemini, and Clarifai for image recognition. The choice depends on the task, the cost per request and where your data is allowed to go.
Can you add AI to an app we already have?
Yes. Most AI features are an API on your backend and a screen in your app, so they can be added to an existing React Native, Next.js or Node.js product.
Will the AI make things up?
It can. To reduce that, answers are grounded in your own data through retrieval, the model is instructed to say when it does not know, and output that carries real risk is reviewed by a person.
How much does an AI feature cost to run?
Model providers charge per request, so the cost grows with usage. We estimate it during the prototype and add per-user limits so it stays predictable.
Is our data used to train the models?
That depends on the provider and the plan. We check each provider's current data policy with you before any customer data is sent to it.
Have a feature in mind?
Book a 15-minute call. We will tell you whether AI is the right tool for it and what a prototype would involve.