AI that does the job, not just the demo
Practical AI built into your business — assistants, automation, and intelligence that save real hours, with the economics that make it sustainable.
[ FIG. 01 ] AI WIRED INTO THE WORK — NOT A CHATBOT BOLTED ON THE SIDE
Most 'AI strategy' is a slide deck and a subscription
It impresses the board and changes nothing, because nobody connected it to the actual work — your data, your tools, your customers.
We build AI that is wired in. A pgvector memory that learns your business over time. Assistants that do not just chat but place orders, pull reports, and trigger workflows. And — critically — a metered credit system so the economics work instead of bleeding money on tokens.
This is not theory. Pulse ships AI memory and content tooling; Roots has a 31-tool assistant that actually runs the register. We implement the version of AI that survives the second month.
What you actually get
An AI assistant that takes actions
Not a chatbot that apologizes — a tool-calling assistant that books, updates, fetches, and reports, role-gated and with undo on every write. The Roots assistant runs 31 such tools today.
Memory that learns your business
A pgvector knowledge layer so the AI knows your products, your docs, and your history — answers get sharper the more you use it, instead of starting from zero every time.
Workflow automation
The repetitive stuff — drafting, tagging, summarizing, routing, enriching — handed to AI that runs in the background so your team does the work only humans should.
Economics that don't blow up
Metered credits, caching, and the right model for each job (not the most expensive one for all of them), so AI is a line item you can predict — not a surprise bill.
Start with the hours, not the hype
Find the hours
Where does your team waste time on work a machine could do? We target real, repetitive cost — not whatever is trending this week.
Prototype
A working proof on your real data, fast, so we are arguing about results instead of slideware.
Wire it in
Connect it to your tools, data, and permissions — grounded, guarded, and with a human in the loop where it counts.
Meter & tune
Credits, caching, and cost controls so it stays affordable, plus evals so it stays correct as it scales.
Under the hood
- RAG / pgvector memory over your own data
- Tool-calling assistants (the Roots 31-tool pattern), role-gated with undo
- Streaming responses + the right model per task
- Content generation, summarization, classification, enrichment
- Metered credit system + usage caps (the Pulse billing pattern)
- Caching + cost controls so tokens don't spiral
- Guardrails, evals, and human-in-the-loop where it matters
- Integrations with your existing tools, CRM, and database
AI that earns its keep
Real AI, in production
Memory, assistants, metered credits, and competitive intelligence — already shipping across all three platforms.
WebJoint Pulse
The operating system for a regulated industry — website builder, CRM, storefront, and AI, multi-tenant from the very first line.
Read the case study →[ R-01 ]Roots POS
A point of sale that treats compliance as architecture, not paperwork — register, inventory, delivery, and seed-to-sale in one system.
Read the case study →[ M-01 ]Menu.com
Four letters. One dot-com. A commission-free marketplace that hands every restaurant the most valuable address in food.
Read the case study →The questions you were going to email
Is this just ChatGPT with my logo?
No. It is AI connected to your data and your tools, able to take real actions — closer to a junior employee who never sleeps than a chat window.
What can AI actually do for my business?
Concretely: answer customers from your real docs, draft and route content, summarize and tag data, run reports on request, and automate the repetitive work that eats your team's week.
How do you keep AI costs under control?
The same way Pulse does — metered credits, caching, usage caps, and matching the model to the task. AI you cannot budget for gets switched off in month two.
Will it make things up?
Grounding it in your own data (RAG) plus guardrails and human-in-the-loop on anything consequential keeps it honest. We build for 'right,' not just 'impressive.'
Which models do you use?
Whatever fits the job — frontier models (Claude, GPT) for hard reasoning, cheaper and faster ones for bulk work. You are not locked to one vendor.
Do I need a whole platform to use AI?
No. We can drop a focused AI feature into your existing site or tools, or build a standalone assistant — start small, prove the hours saved, then expand.