AI agents & assistants
An assistant that answers from your data, and shows its source
A general chatbot bolted onto your website will confidently invent your refund policy. We build retrieval-grounded assistants that answer only from documents you approve, attach the source to every answer, and say "I don't know, here is a human" when the question is outside what they can defend.
Who this is for
You are probably here because
Your team answers the same forty questions every week from documents nobody reads.
You tried an off-the-shelf chatbot and it made something up in front of a customer.
You have real expertise sitting in PDFs, and no way to make it available at 2am.
What you get
Everything below is in the scope, not the upsell
A retrieval layer over your own content
Your documents, policies, manuals and catalog: chunked, embedded and indexed. The model answers from what you gave it, not from what it half-remembers from the internet.
Citations on every answer
Each response links back to the passage it came from. Your team can audit it, and your customer can verify it. This is the single feature that turns a demo into something you can put in front of a client.
Refusal behavior you define
The most important engineering in this work is deciding what the system must not answer. Legal, medical, financial or safety-critical questions get a defined handoff instead of a confident guess. We built exactly this into our own product.
An evaluation set, not a vibe check
We write a test set of real questions with expected sources, and score changes against it. Without one you are shipping prompt edits on feel, and every "improvement" silently breaks something else.
Handoff to a human, cleanly
Conversation history, the customer's question and the sources it looked at, handed to your inbox, Slack or CRM. Nobody has to ask "so what did you already try?"
Cost and latency you can live with
Model choice, caching and prompt design tuned to your traffic. We show you the per-conversation cost before you commit to a plan.
Proof
Where we have done this before
Real projects. Every claim on their pages is one we can evidence.
QuranRI (with VIqra Educational & Welfare Services)
QuranRI: a grounded AI learning platform
A retrieval-grounded AI tutor that answers from verified sources, cites them, and knows when to hand a student to a human.
- RAG architecture
- Vector search
- Next.js
- TypeScript
TraderMind
TraderMind: market analysis platform
Real-time market data, streaming charts and a configurable analysis dashboard.
- Python
- WebSockets
- React
- MongoDB
How it works
Four steps, with dates attached
- 01
Scope
3–5 daysA 20-minute call, then a written scope with fixed price and dates. Free.
- 02
Design
1–3 weeksWireframes, then interface design you sign off before anyone writes code.
- 03
Build
3–12 weeksWeekly demos on a live staging URL. You see progress, not status reports.
- 04
Launch & support
OngoingDeployment, monitoring, and a named person who answers you.
Why us
The four things every US buyer asks, answered up front
These are the questions that decide whether an agency gets hired. Almost nobody answers them on their website. We do, before you have to ask.
Open 9:00 AM – 6:00 PM, Monday to Friday
Our working day, on a calendar you can book: not "we're flexible". Calls, screen shares and decisions happen inside it, and anything urgent outside it has a named person and a phone number rather than a shared inbox.
You never pay for work you have not seen
An advance to begin, then one payment per phase, each scoped and approved in writing before it starts, demonstrated before it is invoiced. Full code and IP ownership transfers on final payment. It is in the contract, not just on this page.
A US contract, under US law
Your agreement is with LabTechCrew LLC, a Texas limited liability company, governed by Texas law. One entity to hold accountable.
You pay us like any US vendor
ACH, domestic or international wire, card through Stripe, Square, PayPal, Wise or a company check. Invoiced in USD with a W-9 on file. Nothing for your finance team to escalate.
FAQ
AI Agents & Assistants: questions
How is this different from just using ChatGPT?
A general model is trained on the whole internet and has no idea which of your policies is current. A retrieval-grounded assistant only reads the documents you gave it, attaches the source to what it says, and can be made to refuse rather than guess. The value is not a smarter model; it is a narrower one that you can audit.
Will it make things up?
Grounding and citations reduce it substantially; nothing removes it entirely, and anyone who tells you otherwise is selling. That is why we build refusal paths, keep a human handoff one click away, and put an accuracy disclaimer in the interface. Our own product does all three.
Do you use our data to train a model?
No. Your content is stored in your own index and used to answer your own questions. Training arrangements, retention and deletion are written into the contract, and we will sign a data processing agreement.
What does it cost to run each month?
Hosting, vector storage and model usage. For most business volumes that lands in the low hundreds of dollars a month. We model it against your expected traffic during scoping so there is no surprise on the first invoice.
Tell us about your ai agents & assistants project
A 20-minute call, then a written scope with a fixed price and dates. Free, and we sign a mutual NDA first if you want one.