Works with the tools you already use
Sound Familiar?
We've automated the easy stuff. But the hard parts — cross-tool correlation, incident context, knowledge retention — still depend on specific people being awake and available.
Your Engineers Are Fighting Fires, Not Building Features
The same engineers shipping your product are also on-call, triaging alerts, and manually debugging deployment failures. That's time they're not spending on the roadmap.
Your Tools Don't Talk to Each Other
Terraform for infrastructure. ArgoCD for deployments. Prometheus for monitoring. Slack for communication. Each tool has its own dashboard, its own alerts, and its own context — none of which connects when something breaks at 2 a.m.
Knowledge Walks Out the Door
When a senior engineer leaves, they take months of operational context with them — why that CronJob exists, which deployment order matters, what that alert actually means. New hires take months to rebuild that understanding from Slack history and tribal knowledge.
You Want AI — But Every Vendor Wants You to Start Over
You've looked at AI tools for DevOps, but they all want you to migrate to their platform, hand over your data, or rebuild your pipelines around their workflow. You just need something that works with what you already have.
What Your Team's Day Looks Like After
We don't replace your engineers or your tools. We give your team an AI layer that handles the repetitive correlation, documentation, and triage work — so they can focus on the decisions that actually require human judgment.
Engineer gets paged → searches logs in three different systems → manually correlates metrics with recent changes → posts status update in Slack → decides on rollback strategy → executes manually → writes up what happened the next morning
Deployment fails → agent analyzes logs, metrics, and recent deployment history in seconds → surfaces the root cause with context → recommends rollback with affected services listed → engineer reviews and approves with one click
No runbooks for common issues → relies on Slack search and asking senior engineers → learning takes months → same questions get asked repeatedly → senior engineers lose time answering them
New team member asks: "Why did the checkout service have errors last night?" → agent explains what changed, what failed, and links to the relevant deployment and alert history → context is instant, not tribal
Weekly review meeting → team manually reconstructs timeline from memory and Slack → critical details are forgotten → incident report gets written once and never updated → same issue resurfaces 3 months later
Incident resolves → agent drafts timeline with contributing factors, affected services, and recommended follow-ups → team reviews and refines → pattern gets added to the knowledge base for future reference
What We Do
DevOps & AI Assessment
- Audit your current toolchain, integrations, and operational workflows
- Identify where your team spends the most time on repetitive toil
- Map high-ROI operational processes ready for custom AI automation
- Deliver a prioritized architecture roadmap with technical recommendations
Custom Agent & MCP Integration
- Design and build custom AI agents tailored for your specific stack and workflows
- Develop custom FastMCP connectors for internal APIs, microservices, and databases
- Implement multi-tier safety governance, dry-runs, and human approval gates
- Run parallel shadow workflows alongside your existing system — zero disruption
Team Enablement & Knowledge Transfer
- Hands-on training and operational drills for engineers, SREs, and platform leads
- Co-author internal runbooks and operational documentation with your team
- Transfer 100% source code ownership — no ongoing vendor dependency
- 60-day advisory support window for technical guidance after handoff
Ongoing Optimization & Advisory
- Periodic performance reviews of agent operations and incident metrics
- Fine-tune agent behavior and prompts based on real operational data
- Expand AI capabilities as your architecture and infrastructure evolve
- Knowledge base quality audits and prompt rubric refinement
Built for Teams Like Yours
Growing Engineering Teams
10–50 engineersThe ad-hoc scripts and manual processes that worked at 5 engineers are starting to crack at 30. You need operational maturity without hiring a dedicated platform team.
DevOps Teams Drowning in Operational Work
Any sizeMore time investigating alerts and correlating dashboards than building infrastructure. Your on-call rotation is consuming your best engineers and nobody has time to improve the tooling.
Teams That Want AI — Without Starting Over
Any sizeYou've looked at AI tools for DevOps. They all want you to migrate to their platform or hand over your data. You need something that layers on top of your existing cloud, infrastructure, and observability stack.
If any of this sounds familiar…
- Your on-call engineers spend more time correlating across dashboards than actually fixing things
- New team members take months to learn your operational context — and that knowledge lives in Slack history
- You've automated the obvious stuff, but edge cases still wake people up at 3 a.m.
- Your runbooks are outdated before the ink dries — nobody has time to maintain them
- You've looked at AI tools, but they want you to rebuild everything around their workflow
…then you're exactly who we built this for.
A Simple, Honest Process
Three phases. Each one delivers value on its own. You decide whether to continue after each phase — no long-term commitment required upfront.
We Listen First
We start by understanding your reality — your tools, your pain points, your team structure. Not imposing a framework.
- Stakeholder kickoff to align on goals and constraints
- Audit your current toolchain and operational workflows
- Identify where your team spends the most time on repetitive work
- Map which processes are ready for AI automation today
We Prove It Works
We pick your highest-impact workflow and deploy agents alongside your current system. Zero disruption risk.
- Deploy AI agents to your most painful workflow first
- Run parallel with existing system — easy to compare
- Measure against baseline metrics your team already tracks
- Train your core team on the conversational interface
Your Team Takes Over
We scale what works, transfer everything to your team, and make sure they can run it independently.
- Roll out remaining AI capabilities based on the roadmap
- Role-specific training for engineers, SREs, and ops leads
- Build your internal knowledge base and operational runbooks
- Full ownership handoff — no ongoing dependency on us
Frequently Asked Questions
See How TalkOps Fits Your Stack
We'll walk through your current setup, identify where AI automation would have the biggest impact, and map out a practical path forward. If it's not a fit, we'll tell you.
Free 60-Minute Assessment Call
Bring your questions. We'll bring honest answers about what's realistic for your environment and team.
No pressure. No sales pitch. Just engineers talking through your challenges.