One API key for Drex, which puts a probability on every call, and NDI, which reads 36 file types and cites the source of every answer.
Works with
Our most accurate setting reads documents as well as the best tool we tested, for less than half the price. Our lightest setting is the cheapest of them all and still beats all but one of the leading AI models.
Parsing leaderboard export, 15 September 2026. Cost is USD per 1,000 pages as measured. ParseBench is scored on its main metric, Content Faithfulness, only.
V
Vishesh Baghel@VisheshBaghell · Sep 25
$499,235 of unbilled work across 1000 work orders. @NaceAI's drex found $482,260.
drex reads the note and the invoice and flags what's missing. code does the math. when drex isn't sure, a human decides.
I
Ivan Fioravanti@ivanfioravanti · Sep 25
Drex: faster, cheaper, better than jev, 32k context and with open weights coming soon? I will surely give it a try!
I’m using Drex as a fast decision layer inside my project Elyreon/NOVA mainly for routing tasks, choosing tools/models, classifying failures, retries, urgency, and handoffs.
the bot already responds sub 1s so i cant imagine how much better drex will make it
I
Israfil@Israfilv2 · Sep 30
Nace shows Drex playing a strategy game. i gave it a harder opponent: my timeline
Spoiler Guard sends each post to the new decision model and blurs the spoilers, 352 post checked in one session with sub-second calls
Using a massive LLM to decide which tool to call feels like hiring a CEO to sort your inbox.
Drex targets those decisions: routing, ranking, classification and guardrails.
Switching was easy. I pointed my existing Jev setup at Drex, kept the same SDK, changed 3 environment variables, and it worked.
I see a good fit for agent routing, tool selection, document classification, and choosing the next action in browser automation.
A
ahmadghoOct 7
i was using jev for playing vs a bot in an old game called Little fighter 2
drex 1.5 is actually very comparable with jev's behaviour in game infact might be better
also it's less latent and very fast i've dropped jev eversince and been optimizing for drex
D
Dean W. Perkins@deanwperkins · Oct 6
someone wired a small open model to a real security camera
389 ms per call
the vision model sees, drex decides
128k context means it can route with real state instead of tiny summaries.
the interesting part isn’t more generation. it’s better decisions before generation starts.
An agent with a Console key reads an AP packet, finds the page that matters and decides what to do with it. Every call in the window is a Console endpoint, and every value comes back with the page it was read from.
Authorization: Bearer $NACE_API_KEY
One key, one credit and one error envelope for both series.
Drex puts a calibrated probability on every option, in one forward pass.
Explore DrexPOST /v1/systemoneINV-88214
state
Invoice INV-88214 bills 1,200 units at $14.10. PO-5512 authorised 1,200 at $13.90. Goods receipt confirms 1,200 delivered, 2 days late.
choicedisposition
a probability per option
noulwithin_price_tolerance
P(yes)0.148
one probability of yes
scorevariance_severity
a distribution over ordered levels
Nace Document Intelligence reads any file and points every value back to its source.
Explore NDIPOST /v1/documents/{task}invoice_2023T210.pdf
Parse
# Invoice 2023T210
| Item | Amount |
| Bookkeeping | 600.00 |
| Total | 600.00 |
Markdown and layout blocks
Split
Page ranges per document
Classify
A label from your taxonomy
Extract
Fields, found or not found
Ground
Total 600.00
p. 1
The page and box it came from
36 file types: PDF, scans, Word, PowerPoint, Excel, CSV, email, HTML, images, audio, video
Read by OCR, transcription and NER models.
Console is plain HTTPS and JSON. Any harness that can call a tool can call it; these are the ones we test with.
Same models, same API, same serving stack at every tier. The only thing that changes is the boundary around your data, from our cloud to your metal.
Your data trains your models. The weights, adapters and eval sets stay yours, inside the boundary you pick.

Start on our GPUs, behind our API, with a key from Console.
For: pilots, evaluations, mid-market teams moving fast.

Your own GPU cluster in our cloud, reached over private links instead of the public internet.
For: regulated teams that are cloud-first but done with shared infrastructure.

The platform installs inside your AWS or Azure account. Data stays within your boundary.
For: banks, Big 4 firms, anyone whose security review starts with “show us the network diagram.”
Talk to sales
Your datacenter, your hardware, zero outbound.
For: government, defense, and sovereign environments where the network cable isn’t there.
Talk to salesCreate a key in Console and send your first request in a minute. When the data cannot leave your network, we bring the platform inside it.