Quantitative General Intelligence

Predict any number from unstructured data.

One model turns text, code, logs, images and tables into a calibrated number — the prediction layer that was missing from your stack.

5 modalities10 domains · SoTA1 unified model
QWM · numeric decoding LIVE
textcall_2024-08-03.txt
codesql_query(orders, …)
logsa100 · kernel launch
image · table▦ ⊞
QWMdecode →
<+><4><·><2><0>
= 4.20
pointwise + densityMedian = 4.20calibrated
01 · the problem

The number you need is trapped in unstructured data.

Today it’s predicted by hand, forced into a brittle table, or never produced at all. The signal is in the raw text, code, logs and notes — but nothing turns it into a decision-ready value.

[ call_2024-08-03.txt ]
tool_callsql_query(orders, ...)
tokensdecoding step 7 / 12
devicea100 · kernel launch

latency? trajectory? token cost?
[ support_chat_88421.txt ]
channelchat · 14 min · 3 transfers
customer“third time this week…”
sentimentfrustrated → escalated

churn risk? CSAT? time-to-resolve?
[ note_MRN-20473.txt ]
hpi62M · post-op day 2 · afib
icd-10I48.91 · Z95.1
medsapixaban · metoprolol

length of stay? readmission? survival?
~90%
of enterprise data is unstructured — and most of it never becomes a number.
Gartner / IDC

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02 · the gap

No single model turns unstructured data into numbers.

The goal is always the same — a calibrated number. But the tooling is fractured across modalities: each one stalls below the gap, and nothing reaches the top.

the goala calibrated number
no model unifies this the layer is missing

Structured

databases, spreadsheets, warehouses
today:

XGBoost, Gaussian processes

Unstructured

documents, transcripts, tickets, notes
today:

LLM prompts, expert opinion

Multimodal

images, video, audio, sensor data
today:

bespoke encoders, custom models

03 · the model

One QWM. State-of-the-art.

A single model spanning five modalities. Every modality breaks through the missing layer and flows into one calibrated number.

the goala calibrated number= 4.20
GQIone model · numeric decoding · calibrated · multimodal
Structured
Unstructured
Multimodal

Cancer Survival

0.738 concordance · SOTA

Code

ρ ≈ 0.9

GPU kernels

16–100× fewer evals

Neural arch. search

+48% over baseline
New

MLIR compilers

ρ 0.99+

Code Static Analysis

≥ 0.85 ρ · 24 langs
New

CPU modeling

ρ ≈ 0.97 zero-shot
New

Data-center efficiency

100× lower error
New

Fusion Simulation

< 10⁻³ error
New

TPU design

Pareto in one pass
04 · in production

Our QWM beats SoTA — and unlocks new capabilities.

Agent Infra Optimization

Trajectory evals · Best-of-N
Accuracy % QWM top-4 full best-of-N det. baseline 99% accuracy ⅓ the compute LLM-call cost (× baseline)
Token reduction
+16%
Agent accuracy

ML Experiment Prediction

Ranking · filtering · hyperparameter opt
Experiment goodness Trials
10–100×
Fewer trials
256×
Lower GPU cost

Clinical Care Capacity

SoTA cancer survival · length of stay
Survival prob. 012243660 Time (months)
↓ LoS
Reduced length of stay
↓ Re-adm.
Lower re-admissions
● In pilot
05 · research

Built on peer-reviewed research.

The peer-reviewed work behind GQI will be shared as it’s published. Details to follow.

PublicationTBD

To be announced

Peer-reviewed research behind GQI — details coming soon.
PublicationTBD

To be announced

Peer-reviewed research behind GQI — details coming soon.
06 · pricing

Simple, usage-based pricing.

Prepaid credits — pay only for what you use, no subscription. Every account starts with $30 free each month. You're billed on input tokens only; the output is a single calibrated number, so it's free.

Free
$30/mo credits

Free every month, no card required — enough to fine-tune and run thousands of predictions.

  • ✓  Full model access
  • ✓  Live fine-tuning on your data
  • ✓  No charge until you exceed it
Start free
Enterprise
Custom

For teams that need it in their own stack.

  • ✓  Dedicated per-tenant models
  • ✓  On-prem / VPC deployment
  • ✓  Volume pricing, SLAs, support
Contact us

Prepaid credits are non-refundable · fine-tune once, serve cheaply · no subscription, cancel by not topping up.

Let’s build the prediction layer.

hello@gqilabs.com