Intelligence
AI app development for businesses that need it working, not demoed
Chatbots trained on your material, agents that finish real workflows, and retrieval systems over documents nobody has time to read. Fixed price, shipped in two weeks.
The gap in AI right now is not capability. The models are good enough. The gap is that almost nobody has connected them to their actual business: their documents, their CRM, their support inbox, the process that eats eleven hours a week.
We build that connection. Not a ChatGPT wrapper with your logo, and not a six-month transformation programme. A specific system that does a specific job, evaluated against real examples before it goes live, and handed to you running on your own API keys.
Every build is model-agnostic by design. We use whichever of GPT, Claude, or Gemini performs best on your task, and the architecture lets you switch later when the ranking changes, which it will.
Who this is for
- Service businesses drowning in the same forty support questions
- Teams with a document library nobody can search
- Operators with a repeatable manual workflow worth automating end-to-end
- Founders adding an AI feature to an existing product
Typical stack
- OpenAI
- Anthropic Claude
- LangChain
- Pinecone
- pgvector
- Next.js
- Supabase
- Vercel AI SDK
Fixed-price services
Every AI app service, with its price and timeline
Pick the tier that matches the scope. Anything outside them is quoted within 48 hours.
AI chatbot
A support chatbot that answers from your own material and escalates when it should.
- Price
- $1,997
- Timeline
- 10 days
AI agent
An agent that finishes a real process across your tools, not one that answers questions about it.
- Price
- $4,997
- Timeline
- 14 days
RAG system
Retrieval over your whole document library, with citations and access control.
- Price
- $5,997
- Timeline
- 14 days
Multi-agent system
Several agents coordinating across a complex process, with orchestration, evaluation, and fine-tuning. Send a brief for a fixed quote in 48 hours.
On-time guarantee
Miss the timeline on a fixed-price build and your deposit comes back. No negotiation, no invoicing games.
What you get
What every build in this category includes
Grounded in your material, not the open internet
Answers come from your documents, your policies, and your product data, with citations back to the source. A model guessing confidently is worse than no system at all, so we build retrieval first and generation second.
Tested against real cases before launch
We build an evaluation set from your actual questions and tickets, then measure accuracy against it. You see the numbers before it touches a customer, and you get the harness to re-run them after any change.
Costed honestly
You get projected monthly token spend at your expected volume during scoping, plus caching and model routing to keep it down. Most support chatbots land between $20 and $200 a month in API cost.
Escalation paths that work
Every system knows what it does not know. Confidence thresholds, human handoff to your inbox or CRM, and logging so you can see what it got wrong and fix it.
FAQ
AI App Development questions, answered
The things people ask on the first call, written down so you do not have to book one.
How much does it cost to build an AI chatbot?
A trained support chatbot is $1,997, a workflow agent is $4,997, and a retrieval system over a large document set is $5,997, which begins with a paid pilot on your own documents. Multi-agent orchestration is quoted individually. Those are build costs: model usage is billed by OpenAI or Anthropic directly to your account, typically $20 to $200 a month.
What is the difference between an AI chatbot and an AI agent?
A chatbot answers. An agent acts. A chatbot tells a customer your refund policy; an agent checks the order, decides whether it qualifies, issues the refund in Stripe, and updates the CRM. Agents need tool access and guardrails, which is why they cost more and take longer.
Which AI model do you use?
Whichever wins on your task. We benchmark candidates against your evaluation set during the build, usually Claude for long-document reasoning and nuanced tone, GPT for structured extraction and tool use. The system is built so the model is a config change, not a rewrite.
Will it make things up?
Hallucination is a design problem, not an inevitability. We ground answers in retrieved source material, cite the source, set a confidence threshold below which it escalates to a human, and constrain scope. It will say it does not know, which is the behaviour you actually want.
Is our data used to train anyone's model?
No. API usage through OpenAI and Anthropic's business terms is excluded from training by default. Your documents sit in your own vector store, on your own infrastructure.
Can it connect to the tools we already use?
Yes. HubSpot, Salesforce, GoHighLevel, Slack, Zendesk, Intercom, Notion, Google Workspace, Airtable, Stripe, and anything with a documented API. Integrations are named in the scope so the price covers them.
Other things we build
Ready to start your AI app build?
Send a brief and get a fixed price and a ship date within 48 hours. If a productized tier fits, you will know today.
No retainer, no hourly billing. Quote in 48 hours.