AI Systems Built for Your Business. Owned by You.

We build custom automations, AI knowledge bases, and in-house replacements for the software you rent every month.

No per-seat pricing. No platform lock-in. You get the code, the data, and a system shaped around how your team actually works.

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Your Business Runs on Workarounds

"We copy data between five tools every day." Someone on your team spends hours moving information from email to spreadsheet to CRM, by hand, and mistakes slip through.
"We pay for software we barely use." Per-seat pricing goes up every year. You use a fraction of the features and still cannot get the one workflow you need.
"Only Sarah knows how that works." Your know-how lives in documents, inboxes, and people's heads. New hires ask the same questions every week.
"ChatGPT doesn't know our business." Generic AI is impressive until you ask it about your products, policies, or customers. Then it guesses.

Every one of these is a solvable engineering problem. Usually with less code, and less money, than you'd expect.

We Built These Systems for Ourselves First

Before taking on client builds, we ran our own AI research operation on custom infrastructure: automated data collection across four AI platforms, a hybrid vector and graph knowledge base, and an in-house analytics product that replaced a paid SaaS category.

100,411
Data events collected by our automated pipeline
165,000+
Unique URLs processed and stored
4
AI platforms driven by browser automation
2
Open-source AI infrastructure projects

Read the Case Studies

Two Subscriptions Cancelled. Over 90% of the Cost Gone.

An Amazon agency managing more than 40 seller and vendor accounts was paying for two analytics platforms: one for P&L reporting, one for Buy Box monitoring. We replaced both with a platform they own.

$2,622 a month

$31,468 a year

Two subscriptions, renewing every year. Years of reporting history locked inside someone else's software.

$204 a month

$2,448 a year

A $180 data feed and a $24 cloud server. Per-SKU P&L, Buy Box alerts in Slack, and more than five years of history exported and kept.

Saving about $2,418 a month, or $29,020 a year (92%).

Real figures, client name withheld. All amounts in USD; the original subscriptions (NZD $55,207 a year) converted at 0.57 USD per NZD, October 2026. Not every tool should be replaced, and part of our first call is telling you honestly when renting is the better deal. Read the case study →

From First Call to Handoff

1

Discovery call (free, 30 minutes)

You walk us through the problem. We tell you whether it's worth building, roughly what it costs, and what we'd do first.

2

Fixed-scope proposal

A written scope, a fixed price, and milestones. No hourly meter running in the background.

3

Build in milestones

You see working software early and often, and you can steer before anything is final.

4

Handoff and ownership

Source code, documentation, accounts, and a walkthrough for your team. Optional retainer if you want us to keep improving it.

More on how we work →

Common Questions

Do I own what you build?

Yes. You get the source code, the database, the documentation, and admin access to every account the system runs on. Nothing is locked to us. If we part ways, the system keeps running.

What kind of businesses do you work with?

Small and mid-sized businesses with a real operational problem: too much manual work, knowledge scattered across documents and inboxes, or a growing stack of monthly subscriptions. You do not need a technical team. We handle the build and hand over something your team can use.

How much does a project cost?

Custom automations start at $1,500. AI infrastructure starts at $5,000. RAG systems start at $7,500. SaaS replacements start at $10,000. Ongoing support is available on a retainer from $2,000 per month. Every project gets a fixed quote before work begins. See pricing.

What is a RAG system?

RAG (retrieval-augmented generation) connects an AI model to your own documents and data, so it answers from your information instead of guessing. We build hybrid systems that combine vector search, keyword search, and knowledge graphs (Graph RAG) so answers stay accurate and cite their sources.

Which AI models do you use?

Whichever fits the job and your budget: Claude, OpenAI models, or open-weight models that can run on your own hardware when data cannot leave your network. Systems are built so the model can be swapped later without a rebuild.

Tell Us What's Slowing Your Business Down

Describe the problem in a few sentences. We'll reply within one business day with whether we can help and what it would take.

Start a Project