Hire chatbot developers who design the handover first
A scripted decision tree is not what buyers mean by chatbot anymore. Our engineers build assistants that answer from your own data, know what they cannot answer, and pass the hard cases to a person.
What you are getting
4 things that decide this
- 01Senior engineers who have shipped AI assistants into live products, not a demo built for the sales call.
- 02You interview every engineer before they start, so nobody is assigned to your team from a profile you never saw.
- 03They design the refusal path before the happy path, because that is the part a scripted bot never had to solve.
- 04If the fit is wrong, we replace the engineer. Every line of code and every prompt they write is yours from the first commit.
What a chatbot developer actually does here
Most of this job happens before the first message is ever sent. Someone decides what the assistant can answer alone, what it must confirm first, and what it hands to a person without making them repeat themselves.
On Broollie our engineers built Max, an assistant that sits inside live meetings and keeps the discussion on track. It writes minutes and action items once the call ends. On Go4Gr8 they built three distinct AI sparring partners for leadership coaching. Each one holds a different role in the conversation and tracks commitments a user makes out loud. On Golancer they built daily AI priorities and forecasts that read a freelancer's actual workload rather than a generic checklist.
Three different products, one repeated decision: what the assistant says when it does not know, and who it tells.
What they take off your roadmap
Grounded answers, not guesses
Retrieval over your own documents and product data, so the assistant answers from what is actually true rather than what a model assumes.
A real escalation path
Rules for when the bot hands off to a person, with the conversation history carried across so the customer never repeats themselves.
Guardrails around the model
Checks before the model answers and checks before the reply reaches a customer, so refusals are a policy decision, not a prompt hoping for the best.
Deflection measured honestly
A scored set of real questions, including the ones the bot should fail. It runs on every release and counts failed sessions, not just completed ones.
- Scoping callFree. What the bot needs to do
- ShortlistEngineers matched to the work
- You interviewYour process, your bar
- EmbedYour repo, standups, tools
- ReviewSwap if the fit is wrong
The interview is yours. A marketplace that assigns a vetted profile is skipping the only step that predicts fit.
Assistants built into live products
How hiring works
- 01
Tell us what the bot needs to do
A free call about the questions it has to answer, the content it should draw from, and where a human needs to take over.
- 02
Meet the engineers
We shortlist people who have shipped assistants into production, and you interview them. Say no and we go back to the shortlist.
- 03
They embed
Your repo, your standups, your ticket system. One engineer owns the assistant's accuracy and is named as accountable for it.
- 04
They hand over
The prompts, the retrieval pipeline, documentation and the scored question set, plus someone on your team trained to run it. The first 2 months of support and maintenance are free, with every build.
Stack
Models and orchestration
Data and infrastructure
Practices
Tell us what your current bot keeps getting wrong
Bring the conversations it mishandles and the content it should have used instead. The scoping call is free, and you leave it knowing whether this is a grounding problem or an escalation problem.
01How is hiring a chatbot developer different from using a job board?
You get an engineer who has already shipped an assistant to production, plus a company accountable if it goes wrong. A job board hands you a candidate and a hiring risk you carry alone. If our engineer is not right, we replace them, which is not a conversation you can have with a contractor you found yourself.
02Will the bot just make things up when it is unsure?
No. We ground answers in your own content through retrieval and set explicit rules for what the assistant must refuse or hand off. A model with no grounding will guess. A confident guess is worse than no answer at all.
03How do we know the deflection rate is real?
We run a scored set of real customer questions against every release, and we count the sessions that failed alongside the ones that completed. A deflection number that only counts finished conversations hides the ones where the bot quietly gave up or stalled.
04Who owns the prompts and the retrieval pipeline afterward?
All of it is yours from the first commit. That includes the prompts, the retrieval setup and the scored question set, which is what tells you months later whether answer quality has drifted.
05What actually drives the cost of a chatbot build?
The escalation logic and the state of the content it draws from, more than the conversation itself. Clean, structured documentation is quick to ground against; scattered content across ten tools is the real work. Scoping calls are free. Where we have to get into an existing codebase before answering, a paid two-week diagnostic produces a fixed price rather than a guess.
