Move Fast –
Understand Faster

Emergent observability that surfaces patterns in dev/staging and explains what matters – catch unknowns before they become production incidents. Built for engineering teams shipping AI-generated code.

See What We Surface
Gonzo real-time log analysis dashboard screenshot (charts and filters)

Three Ways ControlTheory Changes Observability

Automatic pattern discovery and intelligent answers – no pre-configuration required.

Surface Emergent Patterns

Emergent observability automatically discovers new behaviors and anomalies as apps rapidly evolve – beyond what dashboards, alerts, and rules were configured to catch. Perfect for teams shipping AI-generated code that creates novel interaction patterns.

Understand Impact Immediately

Distill system behavior into clear impact and severity – so teams know what matters and what can wait. Get immediate context during incidents instead of correlating 6+ dashboards manually.

Get Answers, Not Dashboards

See what’s wrong and why and get direct answers with evidence for your whole team – developers, SREs, customer success. Explain what’s happening and why it matters – delivering actionable intelligence instead of dashboards to decipher.

Community testimonial logos for ControlTheory and Gonzo

TUI tool for log analysis. It looks cool and seems
really good. It even has a heatmap.
It can also receive logs in real-time via
OpenTelemetry. It’s super modern. Yay yay!

It’s exactly what I’ve been dreaming about as the
ideal UX for logs analysis in Uncloud CLI/TUI.

This is a great tool and it immediately became
part of my toolset.

I decided to give it a shot. It’s really nice! One of
the things I always loved about datadog’s log
analysis tool was its ability to surface log patterns.

Great tool ! awesome job!

Dstl8 distillation flask icon (distill logs into incident insights)
Gonzo terminal UI screenshot with log heatmap and pattern extraction
Dstl8 logo (ControlTheory observability distillation)

ControlTheory Dstl8 surfaces emergent patterns automatically – even when nothing was configured to watch for it. Built for engineering teams shipping AI-generated code, Dstl8 emergent observability discovers unknown behaviors in dev/staging before they become production incidents. Powered by Möbius AI, our three-layer architecture that distills telemetry, identifies patterns, and answers “what’s wrong and why” in real time.

Surface Emergent Patterns Automatically
Understand Impact Immediately
Get Answers, Not Dashboards
Surface. Understand. Answer.
See What We Surface
Gonzo AI-powered insights icon for log patterns and summaries
Dstl8 Slack alert screenshot with incident summary context
Möbius AI logo (continuous AI inside Dstl8)

ControlTheory’s Möbius AI is the multi-layer, continuous AI inside Dstl8, that distills, correlates, and investigates in real time. Reduces raw telemetry into structured summaries of sentiment, severity, and signal flow. Across clusters, it inferences, aggregates and correlates patterns and trends. And at the agentic layer, Möbius agents analyze, explain, and learn from every signal with MCP server open access.

Edge Distillation Layer: compress signals into a compact, contextual format AI can actually use
Operational Inference Layer: SLMs connect what matters across environments
Continuous Agentic Layer: Agents explain incidents, take action in real time
Learn More
Gonzo quick start icon for real-time log analysis TUI
Gonzo in-terminal log analysis view (live charts and patterns)
Gonzo logo (open-source log analysis TUI)

Gonzo – built by ControlTheory – is an open source, real-time log analysis TUI inspired by k9s. Analyze log streams with beautiful charts, AI-powered insights, awesome filtering – all from your terminal.

Real-Time Analysis
Interactive Dashboard
Advanced Filtering
AI-Powered Insights
More Gonzo

ControlTheory Integrations

ControlTheory integrates with all your existing log sources – distilling and analyzing all your logs directly at the edge or live tailing from your monitoring tools – from development to production.
Learn more about our integrations…

Built for High Velocity Teams

Engineering Teams Using AI Coding Tools

AI-generated code creates the most acute monitoring gap – this is where ControlTheory shines.

Cursor, Claude Code, Copilot users
Deploying 5-10x faster than traditional development
Creating novel patterns that pre-configured monitors miss
Need to catch emergent behaviors in dev/staging
SRE and DevOps persona (find problems faster from log data)

Fast-Moving Engineering Teams

Even without AI tools, modern development velocity outpaces manual monitor configuration.

Teams deploying multiple times daily
Microservices with complex interactions
Distributed systems with emergent behaviors
Any environment where change > monitoring capacity
Developer persona (incident summaries, timeline, root cause context)