Langclaw AI

Langclaw
Langclaw turns one research topic into a verifiable AI brief with live sources, agent reasoning, and 0G-backed evidence.

Langclaw is an agentic research platform for builders, founders, and ecosystem teams. A user enters one topic, and Langclaw’s multi-agent research engine discovers live public signals from sources such as X, GitHub, documentation pages, and HackQuest, then ranks trends, writes a concise research brief, and shows the source trail behind the recommendation.

The project solves the problem of noisy, fragmented, and unverifiable trend research. Instead of manually scrolling through posts, repositories, and docs, teams can get a structured brief with evidence-backed findings, a suggested build angle, and verification metadata.

Langclaw uses 0G Storage to store evidence bundles, 0G Chain to anchor the final brief hash when configured, and 0G Compute Router for AI inference and final answer synthesis. This makes the research output easier to verify, reproduce, and trust.

During the hackathon, we focused Langclaw into a clear agentic research engine instead of a generic chatbot. We built the core SignalGraph workflow: one topic input, live source discovery, source normalization, trend scoring, evidence packaging, verification, and final brief generation.

We also integrated the main 0G components needed for verifiable AI research. Langclaw uses 0G Compute Router for AI inference, 0G Storage for storing evidence bundles when configured, and 0G Chain for anchoring the final brief hash when the registry contract is deployed. The backend also includes wallet authentication, API key support, usage metering, memory, scheduled automation, and OpenAI-compatible /v1 proxy endpoints.

By the end of the hackathon, the project had a working platform structure with a frontend dashboard, backend API, Langclaw agent pipeline, source-backed research output, and proof fields for storage and chain verification.

Langclaw is currently not fundraising.

The project is in the hackathon/MVP stage and is focused on validating the product, demo flow, technical architecture, and user demand. External fundraising is TBD after more user testing, stronger traction, and a clearer go-to-market plan.