ENTERPRISE SAAS // CASE STUDY
PROJECT CATALYST.
AUTONOMOUS TIER-3 SUPPORT AGENTS.
SQUAD LEAD
Avinash Singh
ENGINEERS
Priya Sharma, David Miller
INDUSTRY
Enterprise SaaS
warning
Business Pain
60% of engineering week wasted on Tier-3 tickets.
60%
RESOURCE DRAIN
lock
block
Engineering Bottleneck
Traditional chatbots couldn't 'act' on production data securely. Read-only systems failed to resolve complex infrastructure issues.
Architecture: Multi-Agent System (MAS)
Powered by AutoGen & MCP
AGENT 01
search
Detective
Analyzes logs, traces, and historical data to identify the root cause of the incident.
AGENT 02 // CORE
terminal
Executor
Sandboxed Python environment to test fixes and apply patches directly.
def apply_patch(env, script):
sandbox.execute(script)
sandbox.execute(script)
AGENT 03
fact_check
Critic
Reviews the proposed execution plan against safety protocols before deployment.
PERFORMANCE IMPACT
45%
TICKETS AUTOMATED
36h
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4min
RESOLUTION TIME