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RosenfeldAI

The Lab

Public builds, open-source tools, and products shipping in the open.

Build control room

Four systems. One operating view.

Select a product to trace the live path from raw input to useful outcome.

DevReins / system map

Human-in-the-loop control for autonomous coding agents.

X25519 · AES-GCM
01 / ingest

Agent event

02 / reason

Encrypted relay

03 / deliver

Human decision

Why the system matters

Intervene from a phone without opening an inbound port.

Products

What I'm Building

DevReins

Human-in-the-loop control for autonomous coding agents.

Beta

A mobile intervention console for AI coding agents running on your own machine. It routes the exact blocking question to your phone with the agent's files and live diff, then lets you approve, redirect, or step into files, Git, terminals, and localhost apps. Claude Code, Codex, and Gemini are tracked natively; other terminal agents can be controlled live. An X25519/AES-GCM encrypted connect-out relay requires no inbound ports.

Node.jsTypeScriptWebSocketE2EEAI AgentsClaude Code

PocketQuant

Institutional-grade trading signals. Free data only.

Building

A free-data quantitative research engine with a composite macro crash-risk score, evidence-weighted SEC EDGAR 13F signals, and a Streamlit dashboard with a safety-railed broker order panel. The project includes 1,400+ tests and a published audit explaining how a look-ahead bug inflated an early backtest—and how it was fixed.

PythonMLStreamlitSchwab APIQuant Finance13F Intelligence

Clausi

AI compliance auditing in one command.

Live

Developer-first CLI on PyPI that scans codebases against EU AI Act, GDPR, HIPAA, and SOC 2 requirements. Its retrieval-augmented pipeline grounds audit-ready findings in the source code and supports bring-your-own-key operation with a cost estimate before each run.

PythonFastAPIGPT-4CLIComplianceAI
Demo video coming soon

ChangeUs

Connecting citizens with their representatives.

Live

Patent-pending civic AI platform that turns a plain-language concern into the government officials responsible for it. A guarded entity-matching pipeline moved match rate from 0% to roughly 80%, while two-layer caching reduced LLM calls about 80%. Live in production with 200+ automated tests.

Next.jsPythonAINLPFull-StackCivic Tech

Follow the build

I post everything I'm building

Dev logs, breakdowns, and behind-the-scenes on YouTube and Instagram under @RosenfeldAI.