Source-backed Froggit

Key Developments in Autonomous Systems (Week of October 21, 2026)**

## Key Findings - Key Developments in Autonomous Systems (Week of October 21, 2026)** - Based on sources from October 21, 2026, the following are significant developments in autonomous systems: - 1. **Parallel Systems Funding**: Parallel Systems closed a $100 million Series C funding round to scale production of its Panther autonomous freight rail vehicle and expand internationally. [Source: Los Angeles Times, https://www.latimes.com/b2b/consumer-goods-retail/story/2026-10-21/parallel-systems-funding-autonomous-freight-rail] - 2. **Elbit Acquisition of ISE**: Elbit Systems acquired Canadian underwater robotics company ISE, strengthening its maritime capabilities in reconnaissance, mine countermeasures, and ant...

Source: https://www.latimes.com/b2b/consumer-goods-retail/story/2026-10-21/parallel-systems-funding-autonomous-freight-rail

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.