Aurora
Council — multi-agent decision system
Aurora is the Council in production: a decision system that convenes a panel of specialist AI agents, has each reason independently, debates and peer-ranks them, then synthesizes one recommendation — with confidence, evidence, and a full audit trail.
- Industry
- High-stakes professional advisory
- Year
- 2025
- What we ran
- Product architecture, AI engineering, delivery
Confidence score
0%avg
Live debate rounds
2 / 3
Verification checks
0%passed
Recommended
Soft-launch — gated to a 10% cohort
Overall confidence: 0.84
Faster to a recommendation you can defend
Audit trail on every recommendation
Less time spent chasing scattered context
The problem
Experts were making high-stakes calls under time pressure, with the context they needed scattered across systems and no second opinion on hand. A single model gave confident but unaccountable answers — a non-starter when the cost of being wrong is measured in real consequences.
How we solved it
We replaced the single model with a panel. Each specialist evaluates the case from its own discipline; a synthesis layer weighs their reasoning, surfaces where they disagree, and produces one recommendation with the rationale attached — never a verdict you have to take on faith.
What it does
A multi-model council where each specialist reasons independently before synthesis
A rationale trail on every recommendation — you can see exactly how it was reached
Confidence scoring, with disagreement flagged rather than averaged away
A reviewer workspace that keeps a human firmly in command of the call
Under the hood
- Multi-model orchestration
- Retrieval & memory
- Reasoning synthesis
- Audit logging
How multi-agent decisions work.
From prompt to verified recommendation.
Input
We take the question and the context.
Specialist selection
A chief model picks the 4–7 advisors that fit.
Live debate
Advisors reason and challenge each other across models.
Peer ranking
Each advisor ranks the others — consensus emerges.
Synthesis
Positions converge into one grounded recommendation.
Plan-B verification
Independent models re-check the call.
Final verdict
A recommendation with confidence, reasons, and sources.
Traceable reasoning
Every step supplied
Cross-model debate
Diverse perspectives
Confidence scoring
Calibrated, not guessed
Evidence pack
Sources in one place
Audit trail
Decisions you can defend
Transparent. Verifiable. Defensible.
Every expert. The best models for the task.
Your AI experts aren't tied to one model. Each role reaches for the right model on every sub-task, then ASD AI synthesizes their answers — grounded in your data, backed by evidence.
Fable 5
Analysis
GPT-5.5
Reasoning
Gemini 3.5 Pro
Synthesis
Perplexity
Research
Grok 4.3
Logic
Llama 4
Local
Embedding
Context
Mistral
Efficiency
Right model, right task
Each expert picks the best model per sub-task
No single-model bias
Strengths combined, weaknesses cancelled out
Grounded in your data
Answers drawn from your systems, not guesses
Evidence on every answer
Citations and reasoning you can verify
How it works
Each expert routes
Every role sends each sub-task to its strongest model
Models do the work
Specialized models run in parallel against your data
ASD AI synthesizes
One grounded answer, with confidence and sources
Many models. One synthesized answer.
Not locked to a single model — each expert draws on the best, grounded in your business.
Trust every decision your team makes.
Every decision your AI expert team makes is verified, evidenced, and governed — so you can act with confidence.
Confidence score
High confidence
Well-supported by data and verified reasoning.
↑ Top 13% of decisions
24
Key inputs
18
Supporting docs
12
Model citations
100%
Traceable
27
Events recorded
0
Manual overrides
All checks passed
12 / 12 controls validated
2 advisors disagreed
Reviewed & resolved · rationale documented
Ready for activation
What would your expert team take on?
Tell us the work that eats your week. We'll show you which AI expert takes it off your plate — working inside your existing systems — and what it saves you.