Plexe
Plexe Models

Models for the messy data
behind real industries.

Specialist models that turn inconsistent supplier data into decisions you can build on. Each one is trained against a written definition and measured on data it has never seen. We are starting with travel.

Benchmark

The only model that's frontier-accurate in under a second.

200 hotels none of the models had seen, one written definition of a room. GPT-5.5 and GPT-6.1 match mlr-1's F1 at 17+ seconds a hotel.

0.26sper hotel, median, end to end
67×faster than GPT-6.1 at the same F1
93.0F1, on par with GPT-6.1 (93.6)
44×cheaper per hotel than GPT-6.1
mlr-1 0.0s
JEV (Typesafe) 0.0s
Llama 3.3 70B open 0.0s
Qwen3 32B open 0.0s
DeepSeek V3.2 open 0.0s
GPT-6.1 0.0s
gpt-oss-120b open 0.0s
GPT-5.5 0.0s
Figure 1. Median seconds per hotel, played in real time.
under 1s 60708090100 50 0.1s1s10s100s every name its own card · 73.6 GPT-5.5 · F1 94.1 · 44s per hotel · $132.11 per 1,000 hotels GPT-5.5 · 44s GPT-6.1 · F1 93.6 · 17s per hotel · $8.72 per 1,000 hotels GPT-6.1 · 17s gpt-oss-120b · F1 89.0 · 26s per hotel · $4.00 per 1,000 hotels gpt-oss-120b · 26s JEV (Typesafe) · F1 86.2 · 0.38s per hotel · $0.62 per 1,000 hotels JEV (Typesafe) · 0.38s DeepSeek V3.2 · F1 68.2 · 5s per hotel · $2.40 per 1,000 hotels DeepSeek V3.2 · 5s Qwen3 32B · F1 59.3 · 3s per hotel · $0.67 per 1,000 hotels Qwen3 32B · 3s Llama 3.3 70B · F1 52.1 · 2s per hotel · $1.39 per 1,000 hotels Llama 3.3 70B · 2s mlr-1 · F1 93.0 · 0.26s per hotel · $0.20 per 1,000 hotels mlr-1 93.0 F1 · 0.26s
Figure 2. B³ F1 against median seconds per hotel, log scale. Shaded: fast enough for live search. Swipe for the rest →
Table 1. Results on 200 blind hotels. Purity: each card holds one room. Completeness: each room sits on one card.
ModelF1PurityCompletenessSeconds per hotel$ per 1,000 hotels
GPT-5.594.192.196.244.0$132.11
GPT-6.193.691.396.017.3$8.72
mlr-193.094.291.90.26$0.20
gpt-oss-120b open89.096.682.425.8$4.00
JEV (Typesafe)86.292.180.90.38$0.62
DeepSeek V3.2 open68.258.781.54.7$2.40
Qwen3 32B open59.351.470.13.1$0.67
Llama 3.3 70B open52.139.078.51.6$1.39
mlr-15,000
JEV (Typesafe)1,613
Qwen3 32B1,493
Llama 3.3 70B719
DeepSeek V3.2417
gpt-oss-120b250
GPT-6.1115
GPT-5.58
Figure 3. Hotels resolved per $1. A million hotels: $200 with mlr-1, $132,110 with GPT-5.5.

Hotels drawn at random from our 1,000-hotel blind benchmark. Costs are list token prices; ours is our usage price. JEV was asked one name at a time. 10 Nov 2026.

Before / after

Same rates. Fewer cards.

American Inn by OYO Colorado City I-20, Colorado City, from the benchmark, resolved in 203 ms. Hover a room to see its names.

Today19 cards
  • Queen Bed Non-Smoking
  • 2 Double Beds Smoking
  • Queen Bed Smoking
  • 2 Double Beds Non-Smoking
  • Queen Bed Accessible
  • ROOM, QUEEN BED
  • ROOM, QUEEN BED, SMOKING
  • ROOM, 2 DOUBLE BEDS, SMOKING
  • ROOM, 2 DOUBLE BEDS
  • DOUBLE TWO DOUBLE BEDS
  • DOUBLE QUEEN BED NON SMOKING
  • DOUBLE QUEEN BED SMOKING
  • DOUBLE TWO DOUBLE BEDS NON SMOKING
  • DOUBLE Accessible-Queen Size Bed
  • Run of House
  • Standard room
  • Standard Quadruple room
  • Standard Double room
  • Standard Sextuple room
With Plexe8 rooms
  • Queen Room6 names
  • Room, 2 Double Beds6 names
  • Queen Room, Accessible2 names
  • Run of House1 name
  • Standard Room1 name
  • Standard Quadruple Room1 name
  • Standard Double Room1 name
  • Standard Sextuple Room1 name
Why it's hard

Room names are language, not data.

  • Signature Suite, Bathtub
  • Signature Suite, Sea View
  • Signature Suite Taj Club, Lounge Access
1 room
Three suppliers, one suite at Taj Lands End. Rules match patterns; wording like this breaks them.

1 in 5

names grouped differently by two labelling passes that followed the same written rules. Naming is a judgement.
Rule enginesDecision model
BuiltPer supplier, by handOnce, for every supplier
Taught byPatterns and code tablesA written definition of a room
New wordingBreaksReads it
New customerRebuilds the workClean rooms from the first call
Pricing

Pay for what you resolve.

Priced per hotel resolved, not per room, supplier or call. Every supplier included.

Usage

$0.20 per 1,000 hotels

  • No monthly fee or minimum
  • $0.15 per 1,000 above 10 million hotels a month
  • Live and batch API, room hierarchy, support
Get a key

Enterprise

Custom

  • Volume pricing above 20 million hotels a month
  • Dedicated GPU and an availability target
  • A shared support channel
Talk to us

A hotel is one hotel's rooms from all its suppliers, resolved once. Prices exclude taxes.

Travel

Starting with travel

Travel inventory reaches you from dozens of suppliers, each describing the same hotel, room and photo in its own way. Our first models resolve that, behind one API.

mlr-1LIVE

Room resolution

Groups every supplier's offers for a hotel by room, and those rooms into room types. Reads names as suppliers write them, with any beds, views and features they send.

Try it on a real hotel →
Image searchCOMING SOON

Image search

An image search model for travel content. Details on release.

Hotel resolverCOMING SOON

Hotel resolver

Resolves each supplier's hotel record to one property, from its name, address and location.

Use the models

Read the docs, try mlr-1 in your browser, or sign in with your API key.