Summarise the whole customer history before you pick up the phone
Condenses a customer's CRM notes, emails and order history into a one-screen brief before a call or visit, so nobody walks in cold.
- How it works
- On demand, when a call or visit is coming up, the system pulls the customer's CRM notes, past emails and order history, and the large model writes a one-screen brief: who they are, what they buy, open issues, the last few interactions, and anything promised but not yet delivered. It replaces twenty minutes of scrolling the CRM.
- Data you need
- A CRM or structured customer record reachable via API or export, with notes actually in it, and/or the email thread history. If your notes are 'called, no answer' three times, the brief will be three lines — no model fixes empty records. If your CRM is an address book with no interaction history, there is nothing to summarise; build the note-taking habit first. Wiring this to Pipedrive, HubSpot or similar is a small integration job, not plug-and-play.
- What to expect
- Summaries are lossy by design: a brief can omit the one detail that matters, and the model weights recent notes over old ones inconsistently. Very long histories may need staged summarisation, which loses more detail. It works only as well as your record-keeping, and since CRM notes contain personal data, under GDPR this processing belongs on EU-hosted infrastructure — which is where it runs.
- Where people stay involved
- The salesperson reads the brief as preparation, not gospel. Anything commercially binding — an old price promise, a past complaint — gets checked against the source record before it is repeated to the customer.
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.
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.
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
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 sales & b2b
All 15 →Draft a quote from a customer's enquiry email and your price list
Turns an inbound enquiry and your price list into a filled-in quote draft for a salesperson to check and send — a document to correct, not a blank page.
Pull the line items out of RFQ emails and PDFs into a spreadsheet
Extracts part numbers, quantities, units and dates from RFQ emails and PDFs into one consistent table, instead of someone retyping them.
Sort incoming sales emails: real enquiry, existing customer, supplier, junk
Tags every email hitting the sales inbox — new enquiry, existing customer, supplier, junk — within seconds, so real enquiries reach the right person.
Grade new leads against your own definition of a good customer
Scores each new enquiry against your written definition of a good customer, with a short 'why' note the salesperson can read and disagree with.
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.