A grounded AI assistant, inside your platform.
Answers your users can trust — drawn from your content, every claim cited. The demo on the right was built in Stellify on standard Laravel. Bring your own codebase in and build the same, on your AI keys, in your repo.
Built live in Constellation — not a mockup. Ask the demo anything about Stellify. Prefer it done for you? We'll build it →
A chatbot guesses. This one cites.
A generic LLM bolted onto your site will confidently invent things. A retrieval-grounded assistant only answers from the content you give it — and shows its work.
Answers your users can trust
Every response is grounded in your own docs, policies, or knowledge base and carries a citation, so people can verify it. No hallucinated facts.
Deflects repetitive support
It answers the “where do I…”, “how does X work” questions instantly, around the clock — before they reach your inbox.
On your data, your keys
Runs on your own AI provider keys and your own content. Nothing routed through us; you stay in control of cost and data.
Slots into what you have
Exposed as a simple API endpoint, so it drops into your existing platform — Laravel, or anything that can call HTTP.
Standard Laravel, exported
Build it in Stellify, export clean Laravel straight to your repo. It's ordinary code — nothing proprietary to rip out later.
No lock-in
You own the code and the data. Walk away whenever you like and keep a working assistant.
Retrieval first, then the answer.
The technique is called RAG — retrieval-augmented generation. In plain terms: before the AI writes a word, it finds the most relevant passages from your content, then answers only from those — and links back to them.
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Your content becomes the source
Docs, help articles, product data — whatever should inform answers — is indexed for fast, relevant retrieval.
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A question retrieves the right passages
On each question, the most relevant excerpts are pulled and passed to the model as grounding.
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The answer comes back cited
The model answers from that grounding and returns numbered sources, so every claim is traceable.
From answering to acting.
A grounded assistant tells your users things. An agent does things — the same foundation, with your tools wired in. It can look something up, create or update a record, call your APIs, and take several steps to finish a task before reporting back.
Takes actions, not just answers
Create and update records, trigger jobs, send messages — real work in your app, not just replies.
Multi-step by design
Chains several tool calls to complete a task, deciding what to do next at each step.
Connected to your systems
Reaches your database, internal services or any API — including tools exposed over MCP.
Delegates to specialists
Hands sub-tasks to focused sub-agents — e.g. a refunds specialist — and uses their result.
The grounded assistant above is live and built. The agentic version is the same machinery with your tools wired in — built on your Laravel, on your own AI keys, using Laravel's native agent + tools support. If that's the shape you need, let's scope it →
One build, lots of ways to use it.
The assistant above is one example. The same retrieval-and-grounding engine powers most of the AI work companies ask us for — pick the shape that fits your product.
AI support that deflects tickets
A front-line assistant that answers from your help centre and policies, around the clock, before questions reach your team.
Chat with your docs
Let customers ask your product documentation in plain language and get cited answers instead of scrolling.
Internal knowledge search
Give staff one place to ask across wikis, runbooks and past tickets — answers grounded in what your company already knows.
Document Q&A and extraction
Question contracts, reports or policies and pull structured facts out of long documents on demand.
Semantic search
Search your catalogue or content by meaning, not just keywords — surfacing the right result even when the words don't match.
AI workflows with tool calls
Go beyond answers — let the assistant take actions in your app: look things up, fill forms, trigger jobs, hand off to a human.
RAG is one example of our AI work — we handle AI integration end to end. See everything we build →
Build it on your Laravel.
Bring your codebase into Stellify and add a grounded assistant on your own AI keys — then export standard Laravel back to your repo. You keep everything.
Rather not build it yourself? Have us build it for you →