Deploy self-planning,
self-healing AI agents.

Give your agent a goal and watch it break down tasks, execute multi-step workflows, handle errors, and recover automatically. All running locally on your machine.

Agents that actually work

Self-planning

Describe your goal in natural language. The agent decomposes it into steps, identifies dependencies, and creates an execution plan.

Self-healing

When a step fails, the agent diagnoses the error, adjusts its approach, and retries — without human intervention. Up to 3 recovery attempts per step.

Multi-tool chaining

Agents can use Deep Research, Code Sandbox, Data Analyst, and other Alabobai tools as part of their workflow. Tools compose naturally.

Full observability

Watch every decision in real-time. Step-by-step execution logs, decision trees, and visual replay for debugging and auditing.

Guardrails built in

Configurable safety limits on execution time, API calls, and resource usage. Agents can't go rogue — they operate within your constraints.

Persistent memory

Agents learn from past executions. Knowledge persists across sessions so recurring tasks get faster and more accurate over time.

See it in action

Watch an agent plan, execute, recover from an error, and complete a complex task autonomously.

Autonomous Agent
agent> Research the top 5 open-source LLMs, compare their benchmarks, create a summary table, and save as PDF

Planning... 4 steps identified
Step 1/4 Using Deep Research to gather LLM data
  Searching 28 sources... Done (18s)
Step 2/4 Using Code Sandbox to parse benchmarks
  Extracting benchmark scores... Done (3s)
Step 3/4 Generating comparison table
  Error: Missing MMLU score for Mistral-Large
  Self-healing: re-querying with targeted search...
  Found missing data from huggingface.co... Recovered
Step 4/4 Rendering PDF report
  Generating report... Done (2s)

Agent completed: 4/4 steps, 1 auto-recovery, 38s total
Saved: llm-comparison-2026.pdf (12 pages)

How it works

1

Define your goal

Describe what you want in natural language — from simple tasks to complex multi-step workflows spanning multiple tools.

2

Agent plans & executes

The agent creates a step-by-step plan, selects the right tools, and executes each step — handling errors and edge cases automatically.

3

Review & iterate

Review the results, step through the execution log, and refine. The agent learns from your feedback for next time.

Technical specifications

Max steps per executionUnlimited (Pro)
Auto-recovery attempts3 per step
Available toolsCross-tool execution stack
Execution timeoutConfigurable (default 5m)
Persistent memorySession or permanent
Execution replayFull visual replay
Local model supportOllama, LM Studio
Data stored in cloudNone

Put your AI to work

Deploy autonomous agents that handle complex workflows while you focus on what matters.