AI chatbots that resolve, not deflect
We build support and sales chatbots on your own content, connected to the systems that hold the real answer, and hand off to a human with the full conversation attached.
How it works
Most chatbot projects fail in the same place: the bot can chat, but it can't check an order, read the right policy, or admit when it doesn't know. We build the unglamorous parts, retrieval over your real documentation, authenticated calls into your CRM and ticketing system, escalation rules, and evaluation before launch. The result is an assistant that closes tickets and books meetings instead of politely restating your FAQ page.
Grounded in your content, not the open internet
Every answer is retrieved from your approved documentation, product data, and policies, with the source shown.
- Retrieval pipeline over your docs, help center, and PDFs
- Citations on every answer so agents can verify fast
- Refuses and escalates instead of guessing
- Content re-indexes automatically when your docs change
Connected to the systems that hold the answer
The bot reads and writes real records, so it can act on a request rather than describe how to submit one.
- Authenticated lookups: orders, subscriptions, tickets, accounts
- Writes back to your CRM, helpdesk, or ERP
- Books meetings and triggers workflows in Leadify
- Per-user permissions honored on every call
Guardrails, handoff, and audit from day one
Built for teams who have to answer for what the bot said six months later.
- Full transcript logging with retention you control
- Topic and tone guardrails plus PII redaction
- Confidence-based handoff with context passed to the agent
- SOC 2 aligned hosting, 99.9% uptime, your cloud or ours
Where teams use it
Built for real revenue work.
Tier-1 support that never sleeps
Order status, billing questions, returns, and troubleshooting handled end to end across chat, email, and WhatsApp. Anything ambiguous reaches a human with the history already summarized.
Website qualification and booking
A sales assistant that asks the qualifying questions your SDRs would, enriches the record, and puts the right rep on the calendar while the visitor is still on the page.
Internal knowledge assistant
One place for staff to ask about policies, SOPs, benefits, or field procedures, with answers scoped to what each employee is allowed to see.
“We had tried a no-code bot for a year and it never got past 20% containment because it couldn't look anything up. Once the assistant could actually read an order and issue a return, the queue dropped overnight.”
FAQ
Questions, answered.
How much does AI chatbot development cost?
Most production chatbots we deliver land between $28,000 and $90,000 as a fixed project cost, depending on how many systems it integrates with and how much content it has to ground on. A single-channel support assistant over existing documentation sits at the low end; a multilingual bot writing into an ERP sits at the high end. We quote a fixed number after a paid two-week discovery, so there is no hourly meter running. Ongoing model and hosting costs are typically $400 to $2,500 a month depending on volume.
How is this different from a no-code chatbot builder?
No-code tools are excellent at answering from a scraped help center and stop there. They cannot authenticate a user, call your order system, enforce your permission model, or be modified when the vendor's roadmap doesn't match yours. We build on your infrastructure with your own code repository, so you can change the retrieval logic, swap the model, or take the whole thing in-house. You own the IP, and there is no per-conversation pricing that punishes you for growing.
How long does it take to launch?
Four to twelve weeks for the first production release. A focused support assistant over existing content is usually live in four to six; a multi-system bot with authenticated actions, several languages, and a compliance review runs eight to twelve. We ship a working prototype on your real content in week two so you are judging behavior, not a slide deck.
How do you stop it from making things up?
Three layers. The model can only answer from retrieved passages in your approved sources, and it is instructed to say it doesn't know when retrieval comes back weak. Every response carries citations, so wrong answers are traceable rather than mysterious. Before launch we run a graded evaluation set of a few hundred real customer questions and tune until accuracy clears the threshold you set, then keep scoring live conversations after go-live.
Keep exploring
More from the Leadify platform.
Ready to build a chatbot that actually closes tickets?
Book a 30-minute scoping call and we'll tell you what's realistic, what it costs, and how fast it ships.