AI agents that
actually do the work
IncidentMind is an AI automation company that designs and ships custom agents, MCP servers, and workflow systems for real operations. We connect AI to your internal tools, approvals, docs, and production environments so your team can automate work safely — not just chat about it.
Companies want AI
automation
not another copilot
Most teams have AI pilots, SaaS bots, and disconnected automations — but the real work still happens manually across ops, support, engineering, and internal workflows. The gap is not ideas. It's execution inside your stack.
Your Work Lives Across Too Many Systems
The real process spans tickets, Slack, docs, CI/CD, dashboards, databases, CRMs, and approval steps. Generic AI tools rarely connect the full workflow end-to-end.
Owned Automation Matters
Teams in finance, healthcare, and enterprise environments need automations they can inspect, govern, and run in their own environment. Black-box SaaS AI often stops the conversation before the project begins.
Copilots Suggest — They Don't Execute
Chat interfaces are useful, but they don't replace workflow design, tool permissions, human approvals, audit trails, and production-safe actions. Companies need automation that can actually move work forward.
AI Agents Need Real Integration
MCP servers, retrieval pipelines, workflow orchestration, and observability are what turn AI into a working system. Without that engineering layer, "AI automation" stays stuck in demo mode.
What IncidentMind automates
Custom AI systems for operations, support, internal tooling, platform workflows, and agent-driven execution — built to fit your environment instead of forcing you into a generic SaaS playbook.
Custom AI Automation Systems
IncidentMind designs end-to-end AI automation for the workflows that matter most to your business. That can include incident response, support operations, internal requests, knowledge workflows, and multi-step operational processes. You own the system, the logic, and the environment it runs in.
- Workflow discovery and redesign for high-friction manual processes
- Agent-powered intake, triage, routing, summarization, and action execution
- Multi-system context aggregation across docs, tickets, alerts, chat, and internal tools
- Human-in-the-loop approvals, guardrails, and auditability
- Self-improving feedback loops so automations get better over time
- Deployment in your environment with company-owned data and controls
MCP Servers & Enterprise AI Agents
Build secure internal AI agents that can read context, call tools, and take safe action across your systems. IncidentMind creates the integration layer that turns foundation models into useful operators for your company.
- Custom MCP servers for DataDog, Confluence, GitHub, Jira, K8s, databases
- Secure sandboxed agent environments with fine-grained permissions
- RAG pipelines over internal documentation, SOPs, tickets, and codebases
- Workflow orchestration with AI-triggered actions and approvals
- Multi-agent architectures for research, triage, and execution
- Observability, logging, and safety controls for agent behavior
- Built on proven open-source MCP and automation tooling
Workflow & Platform Automation
AI agents only work when the surrounding platform is real. IncidentMind helps modernize the pipelines, integrations, environments, and observability needed to automate delivery, support, operations, and data-heavy workflows in production.
- Workflow orchestration for support ops, incident ops, and internal service requests
- CI/CD automation: parallelization, approvals, release safety, and deployment workflows
- Infrastructure automation with Terraform / CDKTF and cloud-native tooling
- Observability for automated systems: dashboards, traces, logs, and SLOs
- Developer and operator experience improvements with internal tooling
- ETL and data pipeline automation for high-volume operational data
Incident Response Automation
Auto-triage, context gathering, runbook execution, escalation routing, and postmortem drafting across your incident workflow.
Internal Tool Agents
Custom agents that search docs, query systems, answer operational questions, and take safe actions through MCP integrations.
CI/CD & Release Automation
Pipeline orchestration, deployment approvals, release summaries, rollback workflows, and faster delivery loops.
Support & Ticket Automation
Routing, enrichment, suggested responses, escalation summaries, and knowledge retrieval for internal or customer-facing queues.
Knowledge & Documentation Automation
RAG pipelines over SOPs, docs, tickets, and codebases that help agents retrieve the right context at the right time.
Back-Office Workflow Automation
Automate multi-step internal processes that span approvals, documents, systems of record, and reporting.
Fractional AI Automation Lead
For teams that need senior leadership to shape an AI automation roadmap without hiring a full-time executive. IncidentMind helps prioritize use cases, define architecture, evaluate vendors, and guide implementation toward real business outcomes.
- AI automation roadmap and opportunity prioritization
- Architecture decision records (ADRs), governance, and technical strategy
- Vendor evaluation: models, platforms, workflow tools, build vs. buy
- Team mentoring on agents, MCP, automation design, and platform readiness
- Operating model design for human approvals, ownership, and support
- Enterprise review board, security, and compliance alignment
From workflow audit to production
No generic discovery theater. IncidentMind works directly with your team to identify the right workflow, design the automation, ship it, and operationalize it.
Discover
Understand where manual work, delays, and context switching are costing your team time. Focus on the workflow, not the hype.
Assess
Map systems, permissions, approvals, and failure modes. Identify where agents, MCP, workflow orchestration, and platform changes are actually needed.
Build
Implement the automation in your environment with iterative demos, real integrations, and production-ready controls.
Operationalize
Roll out with documentation, observability, training, and ownership so the system keeps working after launch.
Built in production
IncidentMind is informed by real operating experience: large-scale systems, enterprise platform engineering, and AI incident automation shipped in environments where reliability matters.
Scaled a platform from zero to $134M acquisition
Built the original EAT24 platform from the first line of code through scale, acquisitions, and real operational complexity. That experience informs how IncidentMind approaches resilient systems and automation today.
- Designed and built the entire technology stack from scratch
- Grew platform to handle millions of food delivery orders
- Led architecture through two acquisitions ($134M → $287.5M)
- Managed high-availability systems with real-time order processing
Shipped AI incident automation in a regulated enterprise
Built cloud-first platform systems and designed an AI-powered incident workflow that reduced MTTR while integrating with real enterprise controls, infrastructure, and compliance expectations.
- Self-improving LLM incident platform with context from DataDog, Confluence, CI/CD, K8s
- ECS → EKS migration with custom ProxySQL Helm charts for HA clustering
- ETL pipeline processing ~12GB of nonprofit data daily across 20+ DB tables
- Full-stack observability with DataDog APM, SLOs, tracing, and k6 load testing
- Navigated enterprise architecture review boards, security, and compliance
Cross-industry leadership across product, platform, and operations
From adtech to HR-tech to food delivery, the through-line has been the same: understand the workflow, build the system, and ship software that holds up in the real world.
- Post-acquisition engineering at Yelp (EAT24 integration)
- HR-tech platform development at Decisely
- B2B gift card marketplace to $5M ARR at CardPool
- Enterprise solutions for media & entertainment (Autodesk, Macromedia)
Custom AI automation,
not another SaaS bot
Built for companies that need automation to fit reality
IncidentMind sits between generic SaaS bots and abstract strategy consulting. We build company-specific automation systems that connect to your tools, respect your constraints, and leave you with software you actually own.
- Teams that need security, governance, and data control
- Companies with unique workflows that don't fit SaaS templates
- Operators who want AI agents to do more than answer questions
- Leaders who want a durable automation asset instead of another subscription
Battle-tested stack
Production technologies IncidentMind uses to build AI automation that can observe, decide, and act inside real systems.
Cloud & Infrastructure
Infrastructure as Code
CI/CD & DevOps
Observability
AI & LLM
Languages
Tools IncidentMind builds & maintains
Open-source projects that reflect how IncidentMind builds practical AI agents, MCP tooling, RAG systems, and automations.
jobspy-mcp-server
MCP server for AI-powered job search across 10+ platforms. Lets AI agents search, filter, and analyze job listings through natural language.
View on GitHublocalrag
Private RAG system for your codebase and documentation. Run locally, zero data leaves your machine. Semantic search over any repository.
View on GitHubmcp-generator
Framework for generating MCP servers from OpenAPI specs. Rapidly build type-safe MCP servers for any API-based tool.
View on GitHubqa-video
Generate flashcard videos with offline neural TTS. Perfect for educational content creation with AI-powered text-to-speech.
View on GitHubn8n-nodes-bun
Custom n8n workflow automation nodes powered by Bun runtime. High-performance workflow steps for the n8n ecosystem.
View on GitHubconfluence-exporter
Export and backup Confluence spaces to local files. CLI tool for data migration, backup, and RAG pipeline ingestion.
View on GitHubNeed AI automation that
works in your environment?
Start with a free 30-minute call to identify the workflow, systems, and constraints that matter most. No vague AI pitch — just a focused conversation about what IncidentMind can automate for your team.