Autonomous Multi-Agent Competitive-Intelligence System

Client: Confidential Mid-Market SaaS

Principal: Mike Van Amburg · Engagement: AI Enablement · Autonomous Multi-Agent System · 90 days

Context

The client’s competitive-intelligence function depended on ad-hoc research and vendor reports. Each package cost ~$20,000 and arrived ~3 months after request. By delivery, markets had shifted; sales leaders were operating on lagging summaries rather than current, trusted evidence. No one fully owned the bottlenecks.

Objective

Collapse cycle time and unit cost while increasing trustworthiness so sales could act on current, verified intelligence during live pursuits.

Intervention

I embedded with stakeholders, learned the end-to-end process, surfaced failure points, then designed, built, and implemented an autonomous competitive-intelligence system. At a high level, it is a multi-agent architecture (15 agents) coordinated by an orchestration agent with RAG ops for memory. It runs entirely in the background, performs analysis and verification, applies fallback on low-confidence items, and publishes decision-grade reports. After implementation, I trained sales leadership and analysts to operate it independently and established lightweight governance around confidence thresholds and exceptions.

Outcomes

Latency: ~90 days ➝ 5–8 minutes
Unit cost: $20,000 ➝ $0.10–$0.30
Labor displacement: >99.9% of manual analyst hours removed
Financial impact: realized and modeled 8-figure annual savings across research and sales ops
Commercial effect: materially faster, evidence-grounded pursuits; leadership navigated with current, verification-aware intelligence rather than retrospective artifacts

Adoption & Transfer

Enablement covered executives, frontline sellers, and analysts. Ownership sits with the business; there is no operational dependency on me. Operating procedures define when to accept, escalate, or re-query outputs based on confidence and materiality.

Why it matters

This reframed intelligence from a retrospective artifact to an operational capability. The organization now runs on minutes-fresh, verified insight at fractional cost—scalable across teams without additional headcount.