Featured
MetricsTicket volume looks impressive on a dashboard and tells you almost nothing. Here's the small set of metrics — mean time to root cause, human-edit rate on drafted fixes, and repeat-ticket rate — that actually show whether the AI is helping or just moving work around.
A look at how the investigation agent correlates a bug report with the actual source files, recent commits and database state to explain what's really going wrong — not just guess.
GovernanceClaude drafts the patch, but a human engineer always reviews and merges it. Here's the human-in-the-loop checkpoint that keeps automated fixes safe in production.
Multi-AgentEach stage of a ticket's life is handled by a purpose-built agent. We break down what each one does, which LLM it calls, and how work hands off between them.
TicketingAutomated triage and severity scoring get tickets to the right queue in seconds. How the system balances speed with accurate categorisation.
ExplainabilityTechnical root cause analysis is translated into plain-language summaries for support leads and customers — without losing the detail engineers need to verify the fix.
ArchitectureThe sandboxing and permission model that lets the investigation agent read real code and databases without ever risking a write it shouldn't make.
IntegrationsThe agent doesn't replace your ticketing tool — it reads and writes into it. How we map ticket state, comments and attachments across three different systems without losing fidelity.
TicketingSeverity alone misses the customer who's about to churn over a minor bug. How tone signals feed into queue priority without turning into a blunt "angry customer" flag that gets ignored.
GovernanceConfidence scoring, silent fallback to a human queue, and why we'd rather the agent say "I don't know" than produce a plausible-sounding wrong root cause.
Case StudyFewer tickets sitting unassigned, faster first response, and one thing that got harder, not easier — a candid look back at rollout, adoption, and where the AI still needs a human.
OnboardingRepository indexing, connecting the database schema, and the review checklist we run before letting the investigation agent touch a single real ticket.