Open Executive is an Apache 2.0-licensed, open-source virtual executive team built by SenteLabsAI. It presents users with one executive persona while an orchestrator routes requests to eight specialists covering strategy, finance, people, legal basics and compliance, operations, marketing, product, and board communications. The system uses Anthropic’s Claude API by default, with claude-sonnet-4-6 for the executive and most specialists and claude-opus-4-7 with extended thinking for strategy, finance, legal, and board work. It can also use OpenRouter or OpenAI-compatible local model servers such as Ollama, LM Studio, vLLM, and llama.cpp. Each specialist retrieves built-in business knowledge and uploaded company documents from separate ChromaDB collections. A background claude-haiku-4-5 process extracts decisions, initiatives, and advice into SQLite after responses, allowing later sessions to receive prior-decision context. A built-in scheduler can surface follow-ups but requires the FastAPI service to run as a single instance to avoid duplicate actions. The stack includes Python 3.11, FastAPI, Next.js 15, Tailwind, ChromaDB, and SQLite. Users can access it through a web interface, CLI, Slack, email, Telegram, Google Chat, or Discord. Local setup requires Python 3.11+, Node 22+, and an API provider configuration; the first start downloads an approximately 90 MB embedding model.
github.com
13 min
2h ago
Open Executive is an Apache 2.0-licensed, open-source virtual executive team built by SenteLabsAI. It presents users with one executive persona while an orchestrator routes requests to eight specialists covering strategy, finance, people, legal basics and compliance, operations, marketing, product, and board communications. The system uses Anthropic’s Claude API by default, with claude-sonnet-4-6 for the executive and most specialists and claude-opus-4-7 with extended thinking for strategy, finance, legal, and board work. It can also use OpenRouter or OpenAI-compatible local model servers such as Ollama, LM Studio, vLLM, and llama.cpp. Each specialist retrieves built-in business knowledge and uploaded company documents from separate ChromaDB collections. A background claude-haiku-4-5 process extracts decisions, initiatives, and advice into SQLite after responses, allowing later sessions to receive prior-decision context. A built-in scheduler can surface follow-ups but requires the FastAPI service to run as a single instance to avoid duplicate actions. The stack includes Python 3.11, FastAPI, Next.js 15, Tailwind, ChromaDB, and SQLite. Users can access it through a web interface, CLI, Slack, email, Telegram, Google Chat, or Discord. Local setup requires Python 3.11+, Node 22+, and an API provider configuration; the first start downloads an approximately 90 MB embedding model.
github.com
13 min
2h ago
Open Executive is an Apache 2.0-licensed, open-source virtual executive team built by SenteLabsAI. It presents users with one executive persona while an orchestrator routes requests to eight specialists covering strategy, finance, people, legal basics and compliance, operations, marketing, product, and board communications. The system uses Anthropic’s Claude API by default, with claude-sonnet-4-6 for the executive and most specialists and claude-opus-4-7 with extended thinking for strategy, finance, legal, and board work. It can also use OpenRouter or OpenAI-compatible local model servers such as Ollama, LM Studio, vLLM, and llama.cpp. Each specialist retrieves built-in business knowledge and uploaded company documents from separate ChromaDB collections. A background claude-haiku-4-5 process extracts decisions, initiatives, and advice into SQLite after responses, allowing later sessions to receive prior-decision context. A built-in scheduler can surface follow-ups but requires the FastAPI service to run as a single instance to avoid duplicate actions. The stack includes Python 3.11, FastAPI, Next.js 15, Tailwind, ChromaDB, and SQLite. Users can access it through a web interface, CLI, Slack, email, Telegram, Google Chat, or Discord. Local setup requires Python 3.11+, Node 22+, and an API provider configuration; the first start downloads an approximately 90 MB embedding model.
github.com
13 min
2h ago
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