Agent-A
By Agent-AAgent-A is a council-intelligence platform that helps teams make faster, clearer decisions by routing business questions through multiple AI models. The models debate, cross-check, and are fused into one bias-audited, actionable recommendation.
- Stage
- Prototype
- Industries
- Telecom
- Education
- Logistics
- Deployment
- Cloud (SaaS)
Why it is worth it
Agent-A differentiates by delivering an out-of-the-box “AI Council” that (1) orchestrates 7+ frontier models, (2) runs a structured debate, (3) synthesizes a single bias-balanced answer, and (4) optimizes token spend —all in a consumer-grade and enterprise-ready interface.
- Slow, Siloed AI Adoption: No-code workspace lets non-technical business units spin up councils for product, policy, or customer-feedback decisions—accelerating enterprise-wide AI rollout.
- Single-Model Blind Spots: Relying on a single LLM leads to possible hallucinations and gaps. Councils pit several frontier, and trained models against each other and surface the best, bias-audited response.
- Bias & Compliance Risk: Built-in audit layer scores every claim for bias and policy breaches, giving enterprises an evidence trail for HR, DEI, and any other regulatory reviews.
- Vendor Lock-In & Cost Spikes: Councils have the optimal mix of paid APIs and on-prem open-source models, cutting spend and avoiding dependence on any single provider.
Opening the deck…
Page 1
Best customer profile
- 1. Company Size
- Mid-market to large enterprises: 500 – 10 000 employees with multiple business units or regional offices.
- 2. Industry Focus
- Primary: Telecommunications
- Secondary: consulting, HR-tech / L&D platforms, and other knowledge-intensive sectors.
- 3. Core Use Cases
- High-stakes, cross-functional decisions—e.g., product roadmaps, policy drafts, customer-feedback synthesis, performance reviews.
- Scenarios where a single LLM copilot is considered untrustworthy or too biased.
- 4. Specific Needs / Pain Points
- “Decision drag” from information overload and conflicting perspectives.
- Requirement for audit trails and bias checks to satisfy compliance, HR, or DEI policies.
- Desire to stay vendor-agnostic and tap the best model for each task without lock-in.
- 5. Economic Buyer & Champions
- Chief Learning/People Officer, Head of Product, Digital Transformation Lead, or Innovation Lab Director
- —people who own the mandate to speed up knowledge work and improve decision quality.
Notable paying customers
- In active pilot discussions with Unitel (https://unitel.mn), Mongolia’s largest telecom
Customer & Revenue • 100 + weekly active power-users; 4 paying SMB customers on recurring plans (>$14 k ARR) with 95 % three-month retention. Product • Shipped Council-Intelligence Engine v1 (Apr ’24) – the world’s first no-code platform that lets users spin up a debating “AI Council” of seven frontier models (o3, Claude-4 , Gemini-1.5 Pro, Grok-3, DeepSeek-R1, Qwen-2.5-32B, o3). delivers 30 % higher factual accuracy vs. the best single-model baseline (HaluEval). • Released Council Builder (Jun ’24) – enterprises can create a domain-specific council trained on proprietary data in <1 hr, turning internal knowledge into an always-on “panel of experts.” Technical Breakthroughs • Invented a Multi-Model Synthesis Protocol that cuts hallucinations & bias by 35 % on BoldBench/TruthfulQA.