14 KiB
14 KiB
JIRA AI Fixer
Executive Proposal
Date: February 2026
Version: 1.1
Classification: Product Documentation
Executive Summary
The Problem
Support teams face growing challenges in resolving Support Cases:
| Challenge | Impact |
|---|---|
| Response time | Initial analysis consumes hours of senior developer time |
| Growing backlog | Issues accumulate while team focuses on urgent demands |
| Variable quality | Dependency on individual knowledge about the code |
| Concentrated knowledge | Few specialists know all modules |
The Solution
An Artificial Intelligence system that:
- Monitors new Support Cases in JIRA automatically
- Analyzes the problem and identifies affected source code
- Proposes specific fixes in COBOL, SQL, and JCL
- Documents the analysis directly in JIRA
- Creates branches with fixes for human review
Expected Result
┌─────────────────────────────────────────────────────────────────────────────┐
│ BEFORE vs AFTER │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ BEFORE AFTER │
│ ────── ───── │
│ Issue created Issue created │
│ ↓ ↓ │
│ Dev analyzes (2-4h) AI analyzes (5min) │
│ ↓ ↓ │
│ Search code (1-2h) Code identified │
│ ↓ ↓ │
│ Investigate cause (2-4h) Cause + suggested fix │
│ ↓ ↓ │
│ Develop fix (2-4h) Dev reviews and approves │
│ ↓ ↓ │
│ Review + deploy Review + deploy │
│ │
│ TOTAL: 8-14 hours TOTAL: 2-4 hours │
│ │
│ ✅ 60-70% reduction in resolution time │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
Why Now?
1. Mature Technology
Language models (GPT-4, Claude, Llama) have reached sufficient quality for code analysis and generation, including legacy languages like COBOL.
2. Competitive Advantage
Leading companies are adopting AI to accelerate development. Those who don't adopt will fall behind in productivity.
3. Manageable Volume
With typical support volumes, the risk is low and the environment is ideal to validate the solution before scaling.
4. Accessible Cost
Operational cost is minimal, especially with free/low-cost LLM options available.
How It Works
Simplified Flow
┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│ Support │ │ AI │ │ Dev │
│ Case │────▶│ Analyzes │────▶│ Reviews │
│ (JIRA) │ │ + Suggests │ │ + Approves │
└──────────────┘ └──────────────┘ └──────────────┘
5min 5min 30min-2h
┌─────────────────────┐
│ JIRA Comment: │
│ - Root cause │
│ - Affected files │
│ - Proposed fix │
│ - Link to PR │
└─────────────────────┘
Real Example
Issue: "Transaction being declined with code 51 even with available balance"
AI Response (in 5 minutes):
📋 AUTOMATIC ANALYSIS
🔍 Identified Cause:
The AUTH.CBL program is comparing the WS-AVAILABLE-BALANCE field
with format PIC 9(9)V99, but the value returned from HOST uses
PIC 9(11)V99, causing truncation.
📁 Affected File:
- src/cobol/AUTH.CBL (lines 1234-1256)
💡 Proposed Fix:
Change WS-AVAILABLE-BALANCE declaration to PIC 9(11)V99
and adjust the comparison in SECTION 3000-VALIDATE.
📊 Confidence: 87%
🔗 PR with fix: bitbucket.example.com/projects/PRODUCT/repos/...
Security: AI Does Not Alter Production Code
┌─────────────────────────────────────────────────────────────────────────────┐
│ SEPARATION OF RESPONSIBILITIES │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ CLIENT Repository (production) │
│ Product-Client-Fork │
│ ├── AI has access: READ ONLY │
│ └── Changes: ONLY by developers │
│ │
│ AI Repository (isolated) │
│ Product-Client-AI │
│ ├── AI has access: READ AND WRITE │
│ └── Purpose: Branches with fix suggestions │
│ │
│ Approval Flow: │
│ 1. AI creates branch in isolated repository │
│ 2. AI opens Pull Request to client repository │
│ 3. HUMAN developer reviews │
│ 4. HUMAN developer approves or rejects │
│ 5. Only then code goes to production │
│ │
│ ✅ 100% of changes go through human review │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
Investment
Pricing Models
| Model | Description | Price |
|---|---|---|
| SaaS | Hosted, managed by vendor | $2,000 - $5,000/month |
| On-Premise License | Self-hosted, perpetual | $50,000 - $100,000 one-time |
| Enterprise | Custom deployment + support | Contact for quote |
ROI Calculation
Senior developer hourly cost: ~$40-80
Average time saved per issue: 6-10 hours
Monthly savings (10 issues): $2,400 - $8,000
SaaS payback: Immediate positive ROI
Enterprise license payback: 12-24 months
Intangible Benefits
| Benefit | Impact |
|---|---|
| Standardization | All issues analyzed with same rigor |
| Documentation | Complete analysis history in JIRA |
| Knowledge | AI learns patterns, doesn't depend on people |
| Speed | Initial response in minutes, not hours |
| Team morale | Devs focus on complex problems, not repetitive ones |
Deployment Options
Option 1: SaaS (Recommended for Quick Start)
✅ Fastest time-to-value (days, not months)
✅ No infrastructure to manage
✅ Automatic updates
✅ Included support
Option 2: On-Premise (For Compliance Requirements)
✅ 100% data stays in your infrastructure
✅ Air-gapped option (no internet required)
✅ Full control over updates
✅ One-time license cost
Option 3: Hybrid
✅ You host, we manage
✅ Balance of control and convenience
✅ Flexible pricing
Security and Compliance
LLM Provider Options
| Provider | Data Location | Compliance Level |
|---|---|---|
| Azure OpenAI | Your Azure tenant | Enterprise |
| Local (Ollama) | Your servers | Air-gapped |
| OpenAI API | OpenAI cloud | Standard |
| OpenRouter | Various | Development |
Compliance Features
- ✅ Data segregation by client/product
- ✅ Complete audit trail
- ✅ Configurable log retention
- ✅ 100% on-premise deployment option
- ✅ Air-gapped deployment available
- ✅ No code sent to public training datasets
Risks and Mitigations
| Risk | Probability | Mitigation |
|---|---|---|
| AI suggests incorrect fix | Medium | Mandatory human review in 100% of cases |
| Team resistance | Low | Position as assistant, not replacement |
| Code security | Configurable | Choose Azure/local for compliance |
| LLM cost increases | Low | Multiple provider options |
Conservative Approach
The system is designed for phased adoption:
Phase 1: Analysis and suggestion only
AI comments in JIRA, doesn't create code
Phase 2: Code generation in isolated repository
Human decides whether to use or not
Phase 3: Automatic Pull Requests
Human still approves
Phase 4: Auto-merge (only for high-confidence fixes)
Only after months of validation
Implementation Timeline
┌─────────────────────────────────────────────────────────────────────────────┐
│ IMPLEMENTATION ROADMAP │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ Week 1-2 Week 3-4 Week 5-6 Week 7+ │
│ ──────── ──────── ──────── ──────── │
│ Setup + Code Business Go-Live + │
│ Integrations Indexing Rules Refinement │
│ │
│ ✓ JIRA ✓ COBOL ✓ Modules ✓ Production │
│ ✓ Bitbucket ✓ SQL ✓ Validation ✓ Adjustments │
│ ✓ Portal ✓ JCL ✓ Testing ✓ Support │
│ │
│ │ │
│ ▼ │
│ LIVE │
│ ~5-7 weeks │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
Solution Differentiators
Why JIRA AI Fixer?
| Aspect | Generic Tools | JIRA AI Fixer |
|---|---|---|
| JIRA Integration | ❌ Manual | ✅ Automatic |
| Domain knowledge | ❌ Generic | ✅ Configurable business rules |
| COBOL expertise | ⚠️ Limited | ✅ Optimized for mainframe |
| Support Case flow | ❌ Doesn't exist | ✅ Native |
| Deployment options | ❌ Cloud only | ✅ SaaS, on-prem, or air-gapped |
| Customization | ❌ Generic | ✅ Fully configurable |
Next Steps
To Get Started
- Schedule Demo - See JIRA AI Fixer in action with your data
- Pilot Program - 30-day trial with limited scope
- Full Deployment - Production rollout with support
Contact
- Email: sales@yourcompany.com
- Demo Request: https://jira-ai-fixer.yourcompany.com/demo
Conclusion
JIRA AI Fixer represents an opportunity to:
✅ Increase productivity of support team by 60%+
✅ Reduce response time from hours to minutes
✅ Standardize quality of analyses
✅ Retain knowledge independent of people
✅ Choose your deployment - SaaS, on-prem, or air-gapped
The timing is ideal: mature technology, flexible deployment options, and proven ROI.
JIRA AI Fixer - Intelligent Support Case Resolution
Ready to transform your support workflow?