Skip to main content

AI Features Overview

Welcome to SyncNow AI

SyncNow Release 6.0 introduces AI Agents for Work Systems - powerful AI assistants that let you interact with your work systems using natural language instead of complex UIs and queries.

🎉 Release 6.0 Flagship Feature

AI Agents transform how you work with Jira, Azure DevOps, ServiceNow, and more. No JQL. No complex filters. Just ask!

Ask questions. Get answers. Get work done.

Image placeholder: Hero image showing AI agents in action across multiple platforms

🤖 💬 ⚡
Natural Language → Intelligent Queries → Instant Answers

What Can AI Agents Do?

🤖 Query Work Systems Naturally

❌ The Old Way

1. Open Jira
2. Navigate to Filters
3. Write JQL:
project = BACKEND AND
priority IN (P0, P1) AND
assignee IN (teamMembers)
4. Export to CSV
5. Open Azure DevOps
6. Build complex query
7. Export results
8. Manually combine in Excel
9. Create pivot tables
10. Share screenshot

⏱️ Time: 15+ minutes
😓 Difficulty: Requires JQL/WIQL expertise
🔄 Reusable: No, must repeat each time

✅ With AI Agents

"Show me all critical bugs from
Jira and Azure DevOps assigned
to the backend team"

⏱️ Time: 5 seconds
😊 Difficulty: Just ask naturally
🔄 Reusable: Save as favorite query

Plus:

  • ✅ Automatic deduplication
  • ✅ Unified format
  • ✅ Real-time data
  • ✅ Share via link
  • ✅ Export any format

Image placeholder: Side-by-side comparison showing old workflow vs. AI agent workflow


📊 Get Instant Analytics

Instead of manual calculations and dashboards:

"What's our team velocity over the last 6 sprints?"
"Average time in status for completed user stories"
"Show me the burndown for current sprint"

Get instant answers with context.


⚙️ Manage SyncNow Through Conversation

Instead of navigating through admin panels:

"Show sync process status"
"What errors occurred today?"
"Create a mapping between Jira and Azure DevOps"

Manage SyncNow configuration and operations via chat.


🎯 Build Custom Agents

Create domain-specific agents for your workflows:

Sprint Planning Assistant
Release Manager Bot
Support Triage Agent
Compliance Checker
DevOps Health Monitor

Available AI Agents

Core Agents

SyncNow includes two production-ready AI agents.

🌐 Work System AI Agents

Query and analyze work systems using natural language

What it does:

  • ✅ Query Jira, Azure DevOps, ServiceNow, GitHub, GitLab
  • ✅ Cross-system aggregations and analytics
  • ✅ Unified search and reporting
  • ✅ Time-based metrics (velocity, cycle time, burndown)

Use it for:

  • Finding work items across systems
  • Analyzing team performance
  • Generating reports
  • Cross-system queries

Example:

"Show all P0 bugs from last week"

Learn more →

⚙️ SyncNow Execution Agent

Manage SyncNow operations through natural language

What it does:

  • ✅ Monitor sync process status
  • ✅ View errors and diagnostics
  • ✅ Control sync processes (start/stop/pause)
  • ✅ Configure mappings and connectors

Use it for:

  • Daily health checks
  • Investigating sync failures
  • Quick configuration changes
  • Mobile management via chat

Example:

"Show sync process status"

Learn more →

Agent Comparison Matrix

FeatureWork System AIExecution Agent
Primary UseQuery work systemsManage SyncNow
Target UsersAll usersAdmins/Operators
Complexity🟢 Simple🟡 Moderate
Setup Time⚡ Instant⚡ Instant
Best ForDaily queriesAdmin tasks

Image placeholder: Architecture diagram showing how the three agents work together


2. SyncNow Execution Agent ⚙️

Manage SyncNow operations through natural language

What it does:

  • Monitor sync process status
  • View errors and diagnostics
  • Control sync processes (start/stop/pause)
  • Configure mappings and connectors
  • Troubleshoot sync issues

Use it for:

  • Daily health checks
  • Investigating sync failures
  • Quick configuration changes
  • Mobile management via chat

Learn more →


How AI Agents Work

Simple 4-step process:

  1. You ask in plain English (or your language)
  2. Agent understands your intent
  3. Agent queries connected systems
  4. You get a formatted answer

Where Can You Use AI Agents?

MCP Integration

AI Agents are accessible via the Model Context Protocol (MCP), enabling integration with any MCP-compatible LLM platform or custom application.

API & MCP Protocol Integration

Model Context Protocol (MCP):

# Connect Claude Desktop, custom apps
http://your-syncnow.com:8765/mcp/v1

REST API:

POST /api/ai-agents/query
{
"agent": "work-system",
"query": "Show P0 bugs",
"format": "json"
}

Features:

  • ✅ MCP protocol support
  • ✅ RESTful API
  • ✅ Authentication (API keys, OAuth)
  • ✅ Comprehensive docs

Integration Examples:

  • Claude Desktop
  • Custom chatbots
  • Python/Node.js apps
  • CI/CD pipelines

See MCP Integration Guide →


Getting Started

Quick Start (5 Minutes)

1. Enable AI Features

Settings → AI Features → Enable AI Agents

2. Configure Work Systems

Already have connectors configured?
✅ AI Agents can use them immediately

Need to set up connectors?
→ See Connector Documentation

3. Start Asking Questions

Web UI → AI Chat
or
Slack → @SyncNow [your question]

4. Try Sample Queries

"Show me all bugs assigned to me"
"What's our team velocity?"
"List sync errors from today"

That's it! 🎉

Full Getting Started Guide →


Common Use Cases

For Development Teams

Sprint Planning:

"What's our average velocity?"
"Suggest stories for next sprint based on capacity"
"Show incomplete work in current sprint"

Bug Triage:

"All critical bugs created this week"
"Bugs not updated in 7 days"
"P0 bugs by component"

Release Management:

"Status of Release 6.0"
"Incomplete user stories for v6.0"
"Generate release notes"

For Support Teams

Incident Management:

"Show all P0 incidents"
"Incidents exceeding SLA"
"Route INC-123 to correct team"

Trend Analysis:

"Incident volume trend last 30 days"
"Most common incident categories"
"Average resolution time by priority"

For Project Managers

Status Reporting:

"Project status across all systems"
"Work completed vs. planned this month"
"Blockers and dependencies"

Team Performance:

"Team velocity trend over 6 months"
"Cycle time by work item type"
"Completed story points by team member"

For Administrators

SyncNow Management:

"Show all sync process status"
"Errors in the last 24 hours"
"Test connection for Jira connector"

Configuration:

"List all mappings"
"Show field mappings for Bug sync"
"What connectors are enabled?"

Example Queries

Work System Queries

# Basic queries
"Show me all bugs assigned to me"
"List user stories in current sprint"
"Find work items created yesterday"

# Cross-system queries
"Show critical issues from Jira and Azure DevOps"
"Find all items assigned to Dave across systems"
"Duplicate issues between Jira and ServiceNow"

# Analytics
"Average time in status for user stories"
"Team velocity last 6 sprints"
"Burndown for current sprint"

# Complex filters
"Bugs assigned to backend team, P0 or P1, not updated in 14 days"
"User stories in Done without linked test cases"
"Incidents created by VIP customers this week"

SyncNow Operations

# Monitoring
"Show sync process status"
"What errors occurred today?"
"Sync history for last week"

# Configuration
"Show all mappings"
"List field mappings for Jira Bug → Azure Bug"
"What connectors are configured?"

# Control
"Start the billing sync process"
"Pause the Azure DevOps sync"
"Retry failed items from last hour"

# Troubleshooting
"Why did sync fail for JIRA-123?"
"Diagnose slow sync performance"
"Show error details for last failed sync"

See Query Examples →


Security & Permissions

Multi-Layer Security Model

Layer 1: User → AI Agent

  • Role-based access control
  • Who can use which agents?
  • Audit logging of all queries

Layer 2: AI Agent → Work System

  • Agents inherit SyncNow connector permissions
  • Only query systems you have access to
  • Field-level security enforced

Layer 3: Data Filtering

  • You only see data you have permission to view
  • Work system permissions respected
  • Custom filtering rules supported

Compliance & Audit

All AI agent interactions are logged:

  • Who asked what question
  • Which systems were queried
  • What data was returned
  • When it happened

See Security Documentation →


Performance & Scalability

Response Times

Typical query performance:

  • Simple query (single system): < 1 second
  • Cross-system query (2-3 systems): 1-3 seconds
  • Complex aggregation: 2-5 seconds

Caching & Optimization

Intelligent caching:

  • Static data (users, projects) cached
  • Recent queries cached (5-min TTL)
  • Automatic cache invalidation

Query optimization:

  • Parallel system queries
  • Result streaming for large datasets
  • Automatic pagination

What's Different from Traditional Tools?

vs. Manual Queries

TraditionalAI Agents
Learn JQL/query syntaxAsk in natural language
Navigate multiple UIsOne conversational interface
Manual result aggregationAutomatic cross-system aggregation
Static dashboardsDynamic, ad-hoc queries
Desktop-onlyAvailable in chat platforms

vs. Reporting Tools

Reporting ToolsAI Agents
Pre-built reportsAd-hoc queries on demand
Schedule-basedInstant, real-time
Fixed visualizationsContext-aware formatting
Single systemMulti-system out of the box
Limited customizationFully conversational

vs. ChatGPT/Generic AI

Generic AISyncNow AI Agents
No work system accessDirect access to Jira, Azure, etc.
No company contextTrained on your data & processes
Public cloud onlyRuns in your environment
Generic answersSpecific, actionable results
No permissionsRespects work system permissions

Roadmap & Upcoming Features

Coming Soon

Rich Media Chat Window (Q2 2026)

  • Inline charts and visualizations
  • Interactive data tables
  • Code syntax highlighting
  • Embedded images and diagrams

Voice Integration (Q3 2026)

  • Voice queries via phone/smart speakers
  • Text-to-speech responses
  • Hands-free operation

Predictive Analytics (Q3 2026)

  • Forecast sprint completion
  • Predict SLA breaches
  • Anomaly detection
  • Proactive alerts

More Connectors (Ongoing)

  • Asana, Monday.com, Linear, Shortcut
  • Custom API connector builder
  • Database connectors (SQL, MongoDB)

FAQ

Q: Do I need to learn a special query syntax?
A: No! Just ask in natural language. The AI understands intent.

Q: What languages are supported?
A: Currently English. More languages coming soon.

Q: Can AI agents create or modify work items?
A: Work System AI Agents are read-only by default.

Q: Where is my data processed?
A: All processing happens within your SyncNow instance. Data doesn't leave your environment.

Q: Can I use AI agents on mobile?
A: Yes! Via chat platforms (Slack mobile app, Teams mobile, etc.) or web interface.

Q: How much does it cost?
A: AI Features are included in SyncNow Enterprise licenses. Contact sales for details.

Q: What if the agent doesn't understand my question?
A: The agent will ask clarifying questions or suggest similar queries. You can also rephrase.


Learn More

Documentation

Resources


Support

Need help?

Found a bug or have feedback?

  • Submit feedback via the AI chat interface
  • Contact your SyncNow administrator
  • Email: product@syncnow.io

Ready to get started?

👉 Quick Start Guide - Set up AI Agents in 5 minutes


SyncNow Release 6.0 - AI Agents for Work Systems