Real answers to the questions buyers ask before signing off on a custom AI project — on privacy, process, pricing, and everything in between.
ChatGPT is a general-purpose AI trained on the public internet. A custom AI chatbot is trained — or more accurately, grounded — on your specific business content: your product catalog, your policy documents, your FAQs, your knowledge base.
This means it can answer questions like "What is the return policy for items bought during sale?" or "Which SKU fits a size M waist of 32 inches?" using your real data — not a generic guess.
We use a technique called RAG — Retrieval Augmented Generation. Here's the plain-English version:
The result: answers that are factually grounded in your content, not hallucinated from general training data.
We can ingest almost any structured or semi-structured content:
If your data is in a format not listed here, tell us — we've handled unusual formats before.
Not automatically. The AI retrieves from your indexed knowledge base — it doesn't update itself based on user chats (which would be a security risk if users could inject false information).
What we do build is a feedback loop: unanswered or low-confidence queries are logged so you can review them and update your knowledge base manually or on a scheduled basis. The index is then re-built with the new content.
This depends on the hosting model we agree on. We offer three options:
No — when using the API (not the consumer ChatGPT product), OpenAI does not use your inputs or outputs to train their models. This is covered under their API terms of service and enterprise data processing agreements.
The same applies to Azure OpenAI, Anthropic (Claude), and Google (Gemini via API). All of these providers operate API access under data processing agreements that prohibit training on customer data.
Yes — and we've built production systems for exactly this scenario (our mylegalware.com product handles confidential trade law cases and investigation files).
For sensitive deployments we implement:
You do — fully. On project completion we hand over all source code, vector index configurations, prompt templates, and deployment scripts. There is no lock-in to our infrastructure or our accounts.
You can run it yourself, have another team maintain it, or continue working with us. The choice is always yours.
Yes. We deliver the chatbot as a lightweight JavaScript widget — a single script tag you paste into your site's HTML. It works on any platform: plain HTML, WordPress, Shopify, Webflow, custom React/Vue apps.
The widget is fully customizable: brand colors, logo, placeholder text, greeting message, and widget position (bottom-right, bottom-left, or inline).
Yes. Common CRM integrations we build:
We use official CRM APIs and OAuth tokens — no credentials are stored in the chatbot code.
Yes — this is one of the most popular use cases for internal knowledge assistants. Employees ask questions directly in Slack or Teams, and the bot answers using your internal documentation, HR policies, onboarding guides, or product specs.
Access can be restricted by Slack channel or Teams team, so different departments see only their relevant documents.
Yes. We expose all AI functionality via a REST API (or optionally WebSocket for streaming). You can build any interface on top — mobile app, internal portal, voice UI, or integrate it into an existing product.
The API includes endpoints for:
We offer two primary models depending on what you need:
We don't charge a "SaaS seat fee" for your end users — you're not paying per user or per conversation unless you're using a cloud AI API that bills per token (which we help you estimate upfront).
After launch, the main ongoing cost is your LLM API usage (e.g., OpenAI charges per token — roughly per word processed). We estimate this during scoping based on your expected query volume.
As a rough guide:
You pay these API costs directly to OpenAI/Azure/Anthropic using your own API key — they don't pass through us.
Yes — we offer a paid discovery engagement (1–2 weeks) where we review your data, define the architecture, and often build a working proof of concept on a subset of your documents.
At the end of discovery you get:
This is fixed-price and the cost is separate from the full project. If you proceed, the discovery work is credited against the full project fee.
A typical project from kickoff to production launch takes 6–8 weeks. Here's how that breaks down:
To kick off a project we typically need:
We don't need your internal developers to be involved unless you want them to be — we handle everything end-to-end.
Yes — and we build this in from the start. We provide an admin panel where you (or your team) can upload new documents, trigger re-indexing, and see which documents are currently indexed.
Re-indexing after a new document upload typically takes a few minutes, not hours. The chatbot is updated live with no downtime.
All project deliveries include a 30-day post-launch support window at no extra cost. During this time we fix any bugs, tune accuracy issues flagged by real users, and answer technical questions from your team.
After 30 days, you can choose:
RAG systems are significantly more accurate than general LLMs for domain-specific questions, but no AI is perfect. We handle this in a few ways:
During the first 30 days post-launch, we actively review logged queries and tune the system based on real usage patterns.
Yes — we sign NDAs before any document sharing or discovery work begins. For regulated industries or clients handling personal data, we also sign a Data Processing Agreement (DPA) that sets out exactly how your data is handled, stored, and deleted.
For enterprise clients we are happy to review and sign your standard vendor agreements rather than requiring you to use ours.
The fastest way is to fill out our contact form. Describe what you're trying to build, what data you have, and your rough timeline — and we'll respond within one business day.
We also offer a free 30-minute scoping call with no obligation. Use the contact form to request one and we'll schedule at a time that works for you.
Tell us about your project. We'll give you a straight answer — no sales pitch, no jargon.
Get in Touch