AI & Automation
Custom GPT & Knowledge Base Solutions without the six-month discovery phase.
We focus on Custom GPTs grounded in your policies and product docs. Written scope, your stack, weekly demos. No account-manager layer.
Support is answering the same custom gpt & knowledge base solutions. Most teams over-scope it. We write acceptance criteria first, then ship in 8-10 weeks when multiple systems need integration with OpenAI in your repo. We work in your repo, not a fork that rots.
Most chatbots should handle fewer intents, not more. Breadth kills accuracy.
We won't ship AI features without a test set and human fallback.
Who this is for
- -Teams that tried a chatbot hackathon and need custom gpt & knowledge base solutions in production.
- -Founders who need custom gpt & knowledge base solutions scoped before the next fundraise narrative.
- -Product leads adding custom gpt & knowledge base solutions with evals, not demo-day features.
- -Support or ops managers automating repeat work via custom gpt & knowledge base solutions.
Problems we solve
- -Custom GPT & Knowledge Base Solutions estimates balloon because acceptance criteria were never written.
- -A previous vendor shipped custom gpt & knowledge base solutions that broke on edge cases in week two.
- -Your team lacks bandwidth to own custom gpt & knowledge base solutions while shipping the core product.
- -Integrations around OpenAI are fragile and nobody owns on-call.
- -Stakeholders disagree on what "custom gpt & knowledge base solutions done" means. Until that is defined, nothing ships.
What we deliver
- -Written scope for custom gpt & knowledge base solutions with explicit in/out of scope
- -Weekly demo, live or recorded, with decisions logged
- -Acceptance checklist signed before production launch
- -Runbook for the failure modes we expect in month one
- -Handoff doc so your team can maintain without us
- -Working implementation in your repo using OpenAI and Pinecone
How we work
- 1.Kickoff: access, repos, and 8-10 weeks when multiple systems need integration target
- 2.Prototype: rough end-to-end path for feedback early
- 3.Harden: edge cases, monitoring, and docs
- 4.Release: go-live support and next-step backlog
Why Futurebits
- -Stack-first: we start with OpenAI unless the audit says otherwise.
- -Direct access to the people writing code or design files.
- -We won't ship AI features without a test set and human fallback.
Frequently asked questions
How is Custom GPT & Knowledge Base Solutions priced?
Fixed scope for sprints (8-10 weeks when multiple systems need integration). Broader work runs as a pod with weekly demos. We quote after a 30-minute scoping call.
What do you need from us to start?
One decision-maker, repo or staging access, and honest constraints (timeline, budget, stack). Existing docs help but aren't required.
Can you stay on after Custom GPT & Knowledge Base Solutions launches?
Yes. Maintenance sprints or a partner retainer. Many teams keep us for the next bottleneck once v1 is stable.
Who on your team works on Custom GPT & Knowledge Base Solutions?
The same small team from kickoff to launch, not a rotating bench. You talk to the people writing code or design files.
What does the first week of Custom GPT & Knowledge Base Solutions look like?
Access, repo setup, and a written scope draft. No build until you sign off on cut lines and the metric we're targeting.
Related services
Custom GPT & Knowledge Base Solutions: page outline
We focus on Custom GPTs grounded in your policies and product docs. Written scope, your stack, weekly demos. No account-manager layer.
Category: AI & Automation
- Introduction
- Point of view
- What you get
- Delivery process
- Why Futurebits
- Frequently asked questions