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Homer Core
Runtime semantic control for AI agents and apps
Homer Core is a runtime semantic control layer for AI agents and applications. Use the thin Python SDK, route requests to Homer Server, enforce policy in real time, and keep end-to-end decision lineage for audit and compliance. Get Server-side policy enforcement at runtime, Semantic/context-aware request analysis, Decision lineage and audit trail. For developers working on enterprise AI. Try the SDK run your first governed invoke : pip install homer-sdk https://pypi.org/project/homer-sdk/
We built Homer Core to solve a practical gap: teams can ship AI fast, but governance is often bolted on too late. Homer Core sits in the runtime path and applies policy, context, and semantic checks before/after model calls.
The SDK is intentionally thin. Intelligence and controls run server-side for consistency, auditability, and easier enterprise deployment. With Homer Core, you get server-side policy enforcement at runtime, semantic/context-aware request analysis and complete decision lineage and audit trail. Tailor made for developers working on Agentic AI.
You can try the public demo quickly with pip install homer-sdk + demo server credentials.
We’d love feedback on developer experience, policy workflows, and enterprise integration needs.
About Homer Core on Product Hunt
“Runtime semantic control for AI agents and apps”
Homer Core was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #154 on the daily leaderboard. Homer Core is a runtime semantic control layer for AI agents and applications. Use the thin Python SDK, route requests to Homer Server, enforce policy in real time, and keep end-to-end decision lineage for audit and compliance. Get Server-side policy enforcement at runtime, Semantic/context-aware request analysis, Decision lineage and audit trail. For developers working on enterprise AI. Try the SDK run your first governed invoke : pip install homer-sdk https://pypi.org/project/homer-sdk/
On the analytics side, Homer Core competes within Artificial Intelligence, Data & Analytics and Data — topics that collectively have 474k followers on Product Hunt. The dashboard above tracks how Homer Core performed against the three products that launched closest to it on the same day.
Who hunted Homer Core?
Homer Core was hunted by Anant Dhavale. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Homer Core including community comment highlights and product details, visit the product overview.
Anant Dhavale
We built Homer Core to solve a practical gap: teams can ship AI fast, but governance is often bolted on too late. Homer Core sits in the runtime path and applies policy, context, and semantic checks before/after model calls.
The SDK is intentionally thin. Intelligence and controls run server-side for consistency, auditability, and easier enterprise deployment. With Homer Core, you get server-side policy enforcement at runtime, semantic/context-aware request analysis and complete decision lineage and audit trail. Tailor made for developers working on Agentic AI.
You can try the public demo quickly with pip install homer-sdk + demo server credentials.
We’d love feedback on developer experience, policy workflows, and enterprise integration needs.