This is a submission for the Hermes Agent Challenge: Build With Hermes Agent
While experimenting with enterprise AI agents, I noticed a common problem:
Contract reviews are painfully manual.
Vendor agreements, NDAs, MSAs, and SOWs often require legal teams to manually inspect:
I wanted to see:
Can an AI agent intelligently decide what to review and when to escalate?
So I built an Enterprise Contract Intelligence Agent powered by Hermes Agent.
Instead of simply extracting text from contracts, the agent plans tasks, invokes tools, reasons through risks, and decides whether a contract actually requires legal review.
The interesting part?
My first version failed badly.
Hermes Agent was escalating almost every contract.
NDAs.
Vendor agreements.
Even low-risk contracts.
Technically the system worked.
Practically?
Completely unusable.
The issue turned out to be simple:
The agent lacked a confidence-based decision layer.
If a single clause looked risky, Hermes escalated immediately.
That created too many false positives.
So I redesigned the workflow.
Now Hermes Agent:
The result:
Hermes now behaves much more like a real enterprise analyst instead of a rule-based script.
Example output:
Contract Type:
Vendor Agreement
Risk Score:
7.2/10
Issues Found:
❌ Missing termination clause
❌ SLA definition unclear
⚠ Liability section weak
Confidence:
89%
Recommendation:
Escalate to Legal Review
For low-risk contracts:
Contract Type:
NDA
Risk Score:
2.1/10
Issues Found:
✅ Confidentiality present
✅ Termination clause present
Confidence:
94%
Recommendation:
Approved
Contract PDF
↓
Hermes Master Agent
↓
Task Planning
↓
Clause Extraction
↓
Risk Detection
↓
Confidence Scoring
↓
Compliance Check
↓
Final Recommendation
1. Read uploaded contract
2. Identify contract type
3. Extract important clauses
4. Detect missing sections
5. Evaluate business risk
6. Calculate confidence
7. Decide escalation
(Adding screenshots/video walkthrough soon 🚀)
Repository:
https://github.com/yourusername/hermes-contract-intelligence-agent
Example decision logic:
class ContractDecisionAgent:
def should_escalate(
self,
risk_score,
confidence
):
if (
risk_score > 0.7
and confidence > 0.8
):
return (
"legal_review"
)
return (
"approved"
)
Hermes Agent sits at the center of the system.
Instead of hardcoding a workflow, I used Hermes for:
Hermes breaks the task into smaller reasoning steps.
Example:
Read contract
↓
Determine type
↓
Extract clauses
↓
Evaluate risk
↓
Decide escalation
Hermes invokes multiple tools dynamically:
parse_pdf()
extract_clauses()
risk_detector()
compliance_checker()
summary_generator()
Different contract types require different reasoning paths, and Hermes dynamically chooses what to do next.
The agent doesn't just summarize documents.
It reasons through:
This felt like a much more realistic enterprise use case for AI agents.
One big lesson from building this:
Agentic systems become useful only when they can decide
what to do next, not just generate text.
That’s where Hermes Agent really stood out for me.
Thanks for reading 🚀