01 / Division

ALEX Intelligence

Applied artificial intelligence for organizations that have to defend their answers. We build the models, valuation systems, and decision tools that turn first-party data into conclusions that hold up under scrutiny.

Capabilities

From raw data to decisions that survive an audit.

A01

Valuation Models

Automated valuation systems benchmarked against portal error, segment by segment, with the MAPE figures to prove it.

A02

Decision Tooling

Internal tools that put model output in front of operators in language they act on — not dashboards nobody opens.

A03

First-Party Data Systems

Pipelines on our own NVIDIA DGX Spark, not a public cloud, that turn your own records — TEA data, market feeds, transaction history — into a defensible asset.

A04

AI Governance

The controls, documentation, and review process that keep an AI program credible to regulators and clients alike.


Signal

Accuracy is the whole argument.

7.8%
Median error
19,486
Unseen sales tested
NVIDIA
Sovereign compute
1st-party
Data sourcing

Median absolute error of 7.77% across 19,486 Austin-area sales that closed March–September 2026 and were never seen in training — a forward holdout, not a random split. Single-family homes 7.5%, townhouses 7.2%, condominiums 10.7%. By price band, single-family: 9.9% below $250k, 6.1% to $400k, 7.2% to $600k, 8.4% to $1M, 13.1% above $1M. Stated 95% prediction intervals contain the sale price 89.9% of the time, measured on the same holdout. Published segment by segment because a blended average hides where a model is weak.


Stack

Sovereign by design. Every model runs on hardware we own.

ALEX Intelligence has fully migrated off Google Cloud. Data, models and inference now live on an on-premises NVIDIA DGX Spark — 64 containerised services, no third-party AI in the production path.

S01 · Compute

NVIDIA DGX Spark

  • GB10 Grace Blackwell superchip
  • 128 GB unified CPU–GPU memory
  • 20-core Arm CPU · 4 TB NVMe
  • DGX OS 7 (Ubuntu 24.04) · CUDA
  • NVIDIA NGC PyTorch containers
S02 · Language

Local large language models

  • Qwen3 30B-A3B Instruct — production reasoning
  • Qwen3 32B · Qwen3.8 27B
  • Qwen3-Coder 30B
  • BGE-M3 multilingual embeddings
  • Ollama serving · Open WebUI
S03 · Perception

Speech, vision & imaging

  • Whisper large-v3 transcription on GPU
  • Piper neural text-to-speech
  • CLIP property-photo classification
  • FLUX-family diffusion image generation
  • Hugging Face Transformers · Diffusers
S04 · Valuation

Models & forecasting

  • XGBoost · LightGBM · CatBoost ensemble AVM
  • Repeat-sales price indices
  • Offer-ladder negotiation models
  • scikit-learn · statsmodels · PyTorch
S05 · Data

Storage & retrieval

  • DuckDB analytical warehouse
  • MinIO S3-compatible object store
  • Qdrant vector database
  • PostgreSQL 16 · Redis 7
  • Polars · pandas · SearXNG private search
S06 · Platform

Operations & security

  • Docker — 64 services, one box
  • Caddy web and API gateway
  • Cloudflare Tunnel — no open inbound ports
  • Authentik single sign-on
  • Direct feeds: MLS (Bridge), county appraisal districts, Lofty CRM, Twilio

Have a problem that needs a model you can stand behind?