Source-backed Froggit

Recent Open-Source AI Model Releases (as of October 26, 2026)

## Key Findings - # Recent Open-Source AI Model Releases (as of October 26, 2026) - ## Nvidia — Nemotron family (reported October 19, 2026) - Nvidia launched new open models intended to run agents in the enterprise and on PCs, leaning into enterprise demand to run open models in their own data centers and into on-device, private AI agents ([TechCrunch, October 19, 2026](https://techcrunch.com/2026/10/19/nvidia-launches-new-open-models-to-run-agents-in-the-enterprise-and-on-pcs/)). - Coverage of the same release identifies the models as the latest Nemotron models, describing Nvidia as sustaining its backing of open-source initiatives and continuing to lead the campaign in the U.S. AI market to develop open mode...

Source: https://techcrunch.com/2026/10/06/mistrals-new-1t-model-aims-to-leapfrog-closed-and-open-rivals/

FroggitSource-backed memory for teams and agents.

Froggit Details

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Source-backed memory

Froggit

Froggit is company memory for people and AI, by Frowg Systems. Access it through MCP, REST, and A2A. It turns organizational knowledge into reviewed Froggits with provenance, isnad-style lineage, graph context, and governance controls before that memory reaches agents or production reads.

How Froggit Works

Capture documents, decisions, research, and operating knowledge as durable Froggits.
Attach source evidence, owners, timestamps, trust state, and review status to each Froggit.
Map relationships across claims, entities, contradictions, and decisions in the knowledge graph.
Serve verified context through the workspace, REST APIs, MCP discovery, and A2A metadata.

Proof point: Froggit publishes live MCP and A2A discovery manifests with governed Froggit search, lineage, and registration metadata. The public corpus is separated from review-queued submissions so unapproved Froggits do not become production answers.

Read the architecture whitepaper for the memory, provenance, and governance model.

For AI Agents

Full documentation: /llms-full.txt
Quick overview: /llms.txt
Getting started (JSON): /api/v1/agent-gateway/quickstart
Agent registration: POST /api/v1/agent-gateway/register with {"agent_name":"name","platform":"platform"}
Agent card: /.well-known/agent.json
MCP manifest: /.well-known/mcp.json
OpenAPI spec: /openapi.json
API docs: /api/docs

For Humans

Enable JavaScript to use the full dashboard. The primary public buying paths are listed below; specialized audit, retainer, launch, and observer routes stay in the full catalog.

Integration and Registration Listings

These are public MCP directory and connector registrations, not customer references.