Agentic Decision
Intelligence
Turn LLMs from single-answer generators into governed expert councils that debate, judge, and deliver enterprise-grade decisions.
The Single-Node
Bottleneck Problem.
Most enterprise AI deployments rely on a single model acting as an all-knowing oracle. For high-stakes decisions, that's a structural flaw rather than a tuning problem.
Tell Me MoreA single LLM can't be trusted with high-stakes decisions.
Key Concerns.
Perspective
No cross-functional viewpoint in the decision logic. One model, one lens.
Reliability
High risk of hallucination and overconfident answers presented as fact.
Security
Opaque constraints and gaps between stated assumptions and engineering reality.
Auditability
Zero transparent audit trail for high-stakes calls.
Efficiency
Cost limitations and resource scaling issues as usage grows.
Consistency
Output quality that varies unpredictably from run to run.
If we don't trust a single human executive to operate without a review board, we shouldn't trust a single AI model to operate without one.
From Generation
to Governance
delphi replicates the rigor of expert review and structured deliberation at software speed.
Debate
Multiple specialized agents challenge each other's findings to surface risks, gaps, and trade-offs.
Judge
A dedicated evaluation model scores outputs against predefined rubrics and confidence criteria.
Deliver
Audit-ready decision logs designed for enterprise governance and board-level review.
Status Quo vs. delphi.
How It Works: The Three Layers of Agentic Decision Intelligence
Layer 01 : Expert Agents
Specialized expert agents analyze the input from distinct professional perspectives like Risk, Solution Architecture, Security & Compliance, Cost, UX, and Engineering. Agents don’t merely answer independently; they are primed to review and critique one another’s findings.
Layer 02 : The Review Board
A structured review board where agents debate, challenge, and refine recommendations:
- Analyze : Every agent reviews the exact same input through its role’s lens.
- Debate : Agents surface trade-offs and argue points of structural disagreement.
- Refine : Evidence, assumptions, risks, and gaps are explicitly captured.
- Consolidate : A single, refined recommendation emerges from the friction.
Layer 03 : The Evaluator (LLM Judge)
An independent model acts as a strict filtering gate, scoring the council’s output against a transparent rubric : Completeness, Accuracy, Business Alignment, Technical Feasibility, Compliance Readiness, Risk Coverage, Cost Efficiency, and Data Confidence. The model delivers a confidence rating and a clear Go / No-Go decision.
Audit-ready
Decisions
Tell Me MoreThe true value isn't deploying more AI, it's orchestrating friction between AIs to decide on the best course.
Decision Pipeline
From raw input to board-ready artifact in five phases.
Raw Input
Submit a PRD, architecture document, or decision workflow.
Divergent Analysis
Parallel role-based agents dissect the input from every angle.
Convergent Debate
Agents collide on trade-offs and points of disagreement.
Judicial Scoring
The independent judge scores the consolidated output against the rubric.
Auditable Output
A final, board-ready decision artifact is delivered.
Every conclusion comes with a record of how it was reached.
delphi eliminates black-box generation. Every decision artifact includes a confidence score, a multi-dimensional evaluation (strategic alignment, risk mitigation, ROI potential, feasibility, compliance, market impact), a finalized recommendation, and a complete audit trail : captured assumptions, identified gaps, and mitigation requirements with clear deadlines.
A Sample
Use Case
Product Requirement Validation
Complete a confidence-scored PRD review, factoring in all key points of evaluation.
Architecture Review
Multi-perspective scalability and integration critique.
Compliance Audit
HIPAA / SOC 2 / ISO risk assessments with full audit trails.
RFP Responses
Structured scoring of completeness and competitiveness.
AI Governance
Traceable, rubric-based evaluation of AI-generated decisions.
Process Design
Failure-mode analysis and iterative refinement.
Code & Design Review
Feasibility and quality scoring before commitment.
Vendor Evaluation
Cost, risk, and fit comparison across options.
A Complete Ecosystem
Supporting the decision Making.
delphi is the central intelligence engine coordinating a modular ecosystem.
How
To Deploy.
delphi can be integrated as a component or layer of your AI solution, or can be housed in your stack on its own.
AOT’s consulting solutions can help you validate the fit and implement delphi in your business operations.
Unshakable Trust & Quality
Absolute Auditability
