Search all your finance paperwork by meaning, not filename
Finds the right invoice, contract or letter by meaning rather than filename or keyword, across languages. Retrieval only — you read the original.
- How it works
- Your invoices, contracts, accountant letters, insurance policies and tax correspondence are indexed with multilingual embeddings and a reranker, so a query like 'the letter about the delayed VAT registration' or 'insurance terms for water damage in the warehouse' finds the right document even when no keyword matches and the documents span several languages. It is retrieval only — no generated answers to get wrong. You get the original documents back, ranked, and read them yourself.
- Data you need
- The document files with extractable text, gathered in one reachable place — a folder tree or a drive export. No labelling or tidy naming required; that is the point. Scanned paper and image-only PDFs have no extractable text and must go through OCR before indexing, a separate step this stack does not provide. In many SMBs a meaningful share of finance paperwork is exactly such scans — plan for that step or accept those documents will not be searchable.
- What to expect
- Results are ranked, not guaranteed: skim the top hits rather than trusting the first one, and keep ordinary keyword or filename search as a fallback for exact references like invoice numbers. Near-duplicates and old versions can rank alongside current ones — last year's insurance policy instead of this year's — so check dates yourself. A document nobody ever saved cannot be found. Everything stays on your own EU-hosted machines, which for finance paperwork is often the whole reason to do this in-house.
- Where people stay involved
- The human always reads the found document — the system never summarises or answers on its own. Access control matters more than review: payroll and finance documents should only be searchable by people cleared to see them.
Which model, and what it costs to run
Qwen3-8B
This job answers while someone waits, so latency comes first: we hold it to a single small card and, within that, take the best independent score on sticking to the document.
- Licence
- Apache-2.0
- Weights at 4-bit
- 5 GB
- Context
- 32K tokens
- Publisher
- Alibaba (Qwen Team)
What the hardware costs
One 48 GB card holds it
- Rent in the EU
- $1.60/hrScaleway, Paris (PAR2)
- Buy the card
- $7,569new, one-off
- Or rent it by the token
- $0.04 / $0.04per M in / out · DeepInfra
Hardware only, third-party prices from 2026-07. The figure excludes the KV cache, which grows with context length and how many people use it at once — sized properly in a conversation, not guessed here. Renting by the token is cheaper up front; why our customers still self-host is below.
Sticking to the document
Measured on public documents, by a model acting as judge. Read it beside the answer rate: the lowest hallucination rates on this board belong to models that simply decline more often.
Independent measurement · Vectara · board updated May 11, 2026
Structured output and tool calls
Measured in a sandbox, on somebody else's functions. It tells you which models are capable of the shape of the job, not which one will survive contact with your API.
Independent measurement · UC Berkeley (Gorilla project) · board updated 2026-04-12
Reading a long document whole
No benchmark measures this
No current benchmark ranks today's open models here. HELMET showed that the popular test — finding a planted sentence — predicts nothing, and its own table has not been rerun on 2026 models.
So we do not show a chart here. We measure it on your own content, in the first week, and you see the result before anything ships.
The API is cheaper per token. Here is why our customers don't use it.
We will not pretend otherwise: renting a model by the token from a serverless API costs less per million tokens than a card we run for you. We show that price on every use-case page. What it does not include is the part a shop with a customer database actually pays for.
- 01
Your data never leaves hardware you can point at
A serverless "we don't retain your data" is a clause in a contract. Running the model on a card in Amsterdam is a fact of architecture: your catalogue, tickets and customer records are never sent to a third party at all. For a GDPR audit, that is the difference between a promise and a floor plan.
- 02
The price cannot move without your say-so
A serverless rate card is somebody else's lever. The provider can raise the price, retire the model, or change the terms, and your cost moves with it. The same model on the same card costs the same next year — you own the number.
- 03
The model cannot be taken away
Hosted APIs deprecate models on their own schedule; the one you built on can be gone in a quarter. An open-weight model on your own hardware runs for as long as you keep the lights on. No vendor can end-of-life it out from under you.
And the price gap closes with volume: past a card you keep busy — very roughly four billion tokens a month — owning is cheaper outright, even before the three reasons above.
Getting a case like this one from a conversation to production takes about two months, and you can stop at the end of any phase.
Also in finance & admin
All 15 →Pull the details off supplier invoices into your bookkeeping
Pulls supplier name, invoice number, dates, line items and VAT out of PDF invoices into records your accounting software can import.
Turn expense receipts into draft expense entries
Turns OCR'd receipt text into draft expense entries — merchant, date, amount, VAT and likely category — for the submitter and finance to confirm.
Sort expenses into your bookkeeping categories
Reads cryptic bank and card descriptions and proposes a category from your own chart of accounts, backed by your past bookings as evidence.
Match incoming bank payments to open invoices
Proposes matches between bank statement lines and open invoices when references are mistyped, names differ or one transfer covers two invoices.
Next
Tell us what your team does by hand
Describe the process that takes the most time. We will say plainly whether a model is the right tool for it.