Stateflow Labs — Runtime Intelligence for Python AI Systems

Open Source · MIT License · Python 3.10+<br>Runtime Intelligence<br>for Python AI

Two open-source SDKs built around one belief — the biggest AI problems in production are not model problems. They are runtime problems.

"Runtime systems don't justify unreliable agents.

They acknowledge that failures are inevitable —

and handle them in a controlled, recoverable way."

No GPU Required<br>No External Services<br>No Cloud Lock-in<br>Pure Python<br>MIT License

// open source sdks

Two SDKs. One mission.

Start lightweight, go deeper when you need to. Both are free, open source, and production-ready.

Entry Level · Start Here<br>ALGOgent Runtime

Lightweight Runtime Intelligence SDK

A self-contained SDK for building resilient automation scripts and AI pipelines. Synchronous, plug-and-play, zero configuration. Drop it into any Python project and get retry logic, state persistence, checkpoint recovery, and confidence scoring without any external services or async overhead.

Runtime Engine<br>Retry + Backoff<br>State Persistence<br>Checkpoint Recovery<br>Confidence Scoring<br>Event Bus<br>Structured Logging<br>Runtime Metrics

Python 3.10+<br>Synchronous<br>JSON State<br>MIT

View on GitHub

Advanced · Advanced Runtime Layer<br>Adaptive Runtime

Runtime Intelligence Layer for Stateful AI Systems

A full async runtime intelligence layer built for production AI systems that need to survive real conditions. Five core engines work together to analyze context, score confidence, make decisions, persist state to SQLite, and recover from crashes automatically — without GPU, without cloud, without heavy ML frameworks.

Context Engine<br>Confidence Engine<br>Decision Engine<br>State Engine<br>Recovery Engine<br>Async Event Bus<br>SQLite Persistence<br>Runtime Metrics

Python 3.11+<br>Full Async<br>SQLite State<br>MIT

View on GitHub

// side by side

Which one is right for you?

Feature<br>ALGOgent Runtime<br>Adaptive Runtime ★

Target use caseAutomation, simple AI pipelinesLong-running AI systems and automation workloads<br>Execution modelSynchronousFull async (asyncio)<br>State persistenceJSON fileSQLite (async)<br>Checkpoint recovery Built-in Built-in<br>Confidence scoring Basic Adaptive (decay + history)<br>Context engine— Risk + stability analysis<br>Decision engine— Rule-based action selection<br>Event bus Sync pub/sub Async pub/sub<br>Structured logging Color-coded<br>Setup complexityZero configMinimal (pydantic, aiosqlite)<br>GPU required Never Never<br>Runs on $5 VPS Designed for it<br>LicenseMITMIT

// real world experiments

Proof Through Execution

These SDKs are not theoretical concepts.

The following examples were executed using real Python code and runtime scenarios.

algogent — sender.py

python -m<br>algogent.examples.sender

SUCCESS

Message<br>Email sent successfully

Status<br>SUCCESS

Provider<br>Gmail SMTP

Execution<br>Completed

ALGOgent Runtime

Existing Automation Script

A third-party Gmail automation script was executed through ALGOgent Runtime without modification.

Existing code reused

Email delivery successful

Pure Python execution

No cloud dependency

No infrastructure required

Real execution result

algogent — sender.py

python -m<br>algogent.examples.sender

FAILED

Message<br>Error sending email

Code<br>535

Reason<br>Authentication Failed

Status<br>FAILED

Error<br>BadCredentials

ALGOgent Runtime

Failure Detection

The same automation workflow was executed after removing Gmail credentials.

Authentication failure detected

Error surfaced safely

Runtime remained stable

Failure path verified

Real failure scenario

adaptive — decision_engine.py

python -m<br>adaptive.examples.runtime

SIMULATION

service_overload<br>throttle_requests

anomaly_detected<br>flag_for_review

timeout<br>cache_warmup

degraded_service<br>health_check

recovery_needed<br>run_recovery

Adaptive Runtime

Runtime Decision Flow

Multiple runtime events were injected into the system to observe contextual decision making.

Context analyzed

Confidence calculated

Action selected

State persisted

Recovery workflow triggered

Runtime simulation

// open development

Built in Public

Stateflow Labs is developed openly on GitHub.

Every feature, experiment, and iteration is visible to the community.

View GitHub<br>Follow Development

// runtime philosophy

"Most AI problems in production<br>are not model problems.<br>They are runtime problems."

Both SDKs are built around the belief that future AI systems need memory that survives crashes,<br>resilience with checkpoints and retry logic, contextual behavior that adapts to real conditions,<br>and confidence awareness — knowing how certain a decision is.

Not just prompts. Not just workflows. Runtime intelligence.