Distributed Agentic Reasoning: AI Workers That Actually Work

Simple AI search (RAG) is great for "Look up Section 3.2." It is terrible for "Analyze these 50 contracts and tell me if our liability risk has increased."

For high-stakes tasks, you don't need a chatbot. You need Distributed Agentic Reasoning.

What are "Worker Agents"?

Think of an agent as a specialized digital employee. Instead of one AI trying to do everything, we build a framework of autonomous agents that work together to solve a problem step-by-step.

The OpsSolved Agent Framework:

• The Researcher: Its only job is to scan documents and gather raw facts. It finds every mention of a specific clause or figure across your entire database.
• The Analyst: It takes the facts from the Researcher and performs the logic. It compares figures, looks for contradictions, and identifies trends.
• The Auditor: This is the "Safety Layer." It checks the Analyst's work against your specific business standards (Logic-Layer Decoupling) and flags any errors.
• The Writer: It compiles the final, human-readable report, ensuring every single claim has a verifiable citation.

Why This Mimics a Senior Team

Just like a real engineering team, our agents use Logic Loops. If the Auditor finds a mistake in the Analyst's reasoning, it sends the task back for correction.

A typical workflow looks like this:

1. Plan: The system breaks your complex request into 5-10 smaller tasks.
2. Research: Agents gather data from multiple sources (PII-anonymized and VPC-secure).
3. Reason: Agents cross-verify facts and execute multi-step logic.
4. Self-Correct: The system reviews its own output before you ever see it.

When Do You Need Agents?

• RAG (Simple Search): Use this for basic Q&A where the answer is in one place.
• Agentic Reasoning (Work): Use this when the answer requires research, comparison, calculation, or compliance auditing across many documents.

Real-World Impact: M&A Due Diligence

In a recent engagement for a major consulting firm, our Agentic Reasoning framework reduced a process that took 10 analysts two weeks down to just 20 minutes.

The agents didn't just "search"—they researched, cross-verified, and wrote the final risk report with 98.4% expert agreement.

Conclusion

Simple search is a toy. Distributed Agentic Reasoning is an industrial tool. If you need AI that can actually solve a problem, you need a framework of workers, not just a search bar.

OpsSolved: The Adults in the AI Room.