Qualtron
4M-context composite model
Specialized small models behind the QAG Engine — 4M-token context for regulated generation where domain precision beats raw scale.
Qualtron — request a demo
Target: later in 2026
Request a demo — early access for teams already running Q-Prime or QAG demos.
Specialists, composed at inference time
Narrow specialists composed deterministically — not one model for every domain.
Generic LLM
One model, every domain
- Web-scrape training data with uncertain provenance
- Domain drift between prompt and ground truth
- Scaling laws demand billions of parameters for marginal gains
Qualtron
Specialists, composed
- Each specialist trained on licensed, regulated-domain corpora
- QAG signals decide which specialist generates — deterministically
- Domain alignment beats parameter count on regulated benchmarks
The generation layer, by design
Composite architecture
Specialized small models compose at inference time. Deterministic hand-off keeps the reasoning chain inspectable.
4M-token working context
Holds full guidelines, overlays, and multi-year files in a single reasoning pass.
Designed for QAG
Plugs in behind the QAG Engine. HSC signals control which specialist generates.
Regulated-domain specialization
Each specialist trained on compliance, contract, and regulatory corpora.
Replaces the generic LLM tier
Specialist models the QAG Engine can prove are relevant and within coverage.
License-safe by construction
Licensed, regulated-industry clean training data — no uncertain web-scrape provenance.
What teams evaluating Qualtron usually ask.
What is Qualtron?
How is Qualtron different from GPT or Claude?
Why a 4M-token working context?
When will Qualtron be available?
Want Qualtron in your evaluation early?
Teams on Q-Prime or QAG demos get first access.