Reasoning That Compounds

Generic AI starts from zero every time. Rivus is domain-specific AI that learns from every task — multi-model reasoning that gets measurably better the more it runs.

See it on your domain

Multi-Model Reasoning

4–8 frontier models (Claude, GPT, Gemini, Grok) collaborate on every task. Cross-validation catches blind spots that any single model misses.

Self-Improvement

Every output is reviewed. Mistakes become behavioral principles. The system extracts what went wrong and encodes corrections that persist across sessions.

Autonomous Operation

Runs 24/7 with supervisor agents that monitor, prioritize, and self-correct. Human-in-the-loop by policy, not by necessity.

The Compound Loop

Each task makes the next one better. This is not prompt engineering — it is systematic knowledge accumulation.

Task
Ingest
Reason
Multi-model
Output
Structured
Learn
Auto-review
Better
Next task
Principles feed back — quality compounds over time
25K+
Learned Instances
664+
Sessions
19
Strategies
20+
Pipelines
4–8
Frontier Models

From a company name to a full investment dossier

One input: a ticker or company name. Rivus fetches SEC filings, earnings transcripts, price history, and competitive data. Multi-model analysis synthesizes a structured dossier with risk scoring — automated, improving, running 24/7. Each dossier refines the pipeline for the next.

01Input: "NVDA"
02Fetch: SEC 10-K, earnings call, price data
03Analyze: 4 models cross-validate findings
04Score: TFTF framework (Threat/Fit/Timing/Flag)
05Output: Structured dossier + risk matrix
06Review: auto-critique, extract 3 principles
07Next run: measurably better

See it on your domain

Deploy alongside your current workflow. No rip-and-replace. Rivus adapts to your data, your processes, your quality bar.

Get a technical walkthrough
Typical deployment: 2–4 weeks from kickoff to first autonomous pipeline