Reads what your team reads
Scanned PDFs, phone photos, spreadsheets, emails and drawings. The agent takes what arrives, in whatever format it arrives.
We build custom AI agents for the document-heavy work your team still does by hand: reading quotes, checking drawings, filling schedules, pricing bids. Each one is built and scored against your own past work before it touches a live job. We also deploy and operate dedicated NVIDIA DGX B300 systems.
We start from a job your team already does and the results they've already produced, then build an agent that does the reading and checking for them. A person still makes every decision that matters.
Scanned PDFs, phone photos, spreadsheets, emails and drawings. The agent takes what arrives, in whatever format it arrives.
Each figure says which document and page it came from and how sure the agent is, so checking it takes seconds.
When a model gets something wrong, we fix it with a tested check in code. A model can't be relied on to follow an instruction every time.
The agent proposes and flags. Your people accept or reject, and every decision is logged with who made it and when.
Before an agent goes near live work, we measure it against what your team actually submitted in the past.
Run on a commercial model API, or on open models hosted on dedicated hardware so your documents never reach a third party.
Built with an electrical contractor whose estimators price large building tenders. It handles the reading and cross-checking that used to take days, and it now runs beside live tenders without changing what the firm submits.
Reads every supplier quote, whether it's a scan, a photo, a spreadsheet, an email or prices handwritten on a printout. Matches each price to the firm's price list and flags big moves from earlier revisions and past tenders.
Reads quantities from the consultant's drawings and checks them against a second count on the same drawing. Where the drawing contradicts itself, it shows the excerpts side by side.
Prices the bill of quantities from this tender's quotes, the firm's past bids and its rate library. Every line says where its figure came from, and lines it can't price are listed with what's missing.
Fills the tenderer's technical offer from the suppliers' own data returns and checks approved makes. Every answer cites its source, and the rows that need an estimator are marked.
A rule-based check of the priced bill before it goes out. No model involved, so the same input always gives the same answer.
Estimators use it alongside their usual workbook. After each submission, every part is scored against what was actually sent, and the tender joins the history the next bid learns from.
Tendering isn't the only fit. Any job where people read a pile of documents, match them against a list and fill in a schedule is a candidate. Tell us about yours.
No big-bang rollout. The agent earns trust on your past work first, then on live work beside your team.
We sit with the people who do the work and collect a few past jobs, with the documents that went in and the result that went out.
We build the agent against those past jobs and measure it on them, so you see how often it's right before anyone relies on it.
It works alongside a live job without changing what you deliver, gets scored after each one, and takes over more as the numbers hold up.
We own and operate NVIDIA DGX B300 systems: eight Blackwell Ultra GPUs per node on NVLink. Our current node is on a long-term dedicated lease. Talk to us about the next one.
A whole DGX B300, bare metal, with your own operating system and network. Fixed monthly rate, long-term.
Data centre, power, cross-connects, firmware and out-of-band management are ours to look after. You get console and power control over a scoped, logged account.
Open models like Qwen, Llama or DeepSeek served on dedicated hardware behind an OpenAI-compatible endpoint, so agents can run without your data leaving it.
Isolated, disposable environments for running an agent's code, with secrets the agent never sees. How they work.
Intel TDX with GPU confidential-computing mode, so memory is encrypted even from us. Being commissioned on this hardware, not enabled yet.
Volumes are encrypted at rest (LUKS2) and cryptographically erased at hand-back, with a certificate you can verify.
| A DGX B300 node | Specification |
|---|---|
| GPUs | 8× NVIDIA B300 SXM6, 288 GB HBM3e each (2.3 TB total), NVLink between all eight |
| CPU and memory | 2× Intel Xeon 6776P, 2 TB DDR5 |
| Networking | 8× ConnectX-8 SuperNIC, 2× BlueField-3 DPU |
| Storage | Local NVMe |
Agents keep an append-only log of what they proposed and what your people decided. You choose where the model runs: a commercial API, or dedicated hardware that we own and run, in one data centre. Volumes are encrypted at rest and crypto-erased at hand-back, with a certificate. Confidential computing is being commissioned, not enabled, and we're not certified against any compliance framework yet. We'll always tell you exactly what's on.
./scripts/tbxcert.py verify TBX-CE-2026-0001