A privacy-first app that strips AI watermarks from content you own.
Graph-Native Infrastructure for Context and Accountable AI Systems
FactCircuit: an auditable claim-and-evidence verification loop with immutable provenance, staged checks, bounded retrieval, and reproducible evaluation.
Remove visible and invisible AI watermarks from images and video, and AI provenance metadata from images, video, and audio. Python library, CLI, and agent skill for SynthID, C2PA, EXIF, IPTC, XMP, and common generative-AI marks.
The open-source governance layer for AI agents: write the rules declaratively, Bernstein enforces them and produces the verifiable, replayable record. Free, Apache-2.0. https://bernstein.run
Finathink — Financial Research Optimizer for auditable, point-in-time research, mathematical learning, and constrained portfolio analysis.
Remove AI watermarks and provenance metadata from text, images and documents. Strips invisible Unicode, C2PA Content Credentials, EXIF/XMP and generator tags from 30+ AI tools. Runs locally, no API key.
An open-source, PyTorch-like runtime for dynamic multi-agent and multi-session workflows.
:mag: ScanCode detects licenses, copyrights, dependencies by "scanning code" ... to discover and inventory open source and third-party packages used in your code. Sponsored by NLnet, the Google Summer of Code, Azure credits, nexB and other generous sponsors!
The official repository for the AiiDA code
Genblaze is an open source Python SDK for orchestrating generative AI media pipelines across video, audio, and image providers with built in provenance for every output.
Browser teleoperation data for embodied AI — elizaOS-ready episodes, trajectory_db converter, onchain provenance. The fuel station for agent robot stacks.
Tamper-evident tracing, policy gates and cross-checks for AI agents: see what the agent did, and why.
Who the good traders on Robinhood Chain are buying: resolved wallets, a 20-second on-chain tape, provenance on every fill, AI verdicts, bursts and exits. Site + Telegram bot + API. Runs on $0/month.
Reliable multi-source financial data ingestion with provenance, retries, normalization, and standard HTML/CSV/JSON reports.
Evidence validation and policy engine for AI-assisted biological curation
Auditable human-feedback annotation, review, provenance, and frozen training-data export.
Autonomous experiment-pipeline orchestrator: versioned research-plan DSL with dependency DAGs, deterministic checkpoint/resumable executor, tamper-evident provenance ledger, UCB1/Thompson schedulers with measured regret against synthetic oracles, ablation bookkeeping, offline report synthesis. NumPy core, CPU-only torch extra.
Python-first systemic-risk research software for evidence-graded, bitemporal dependency graphs. Import JSON, CSV, GraphML, or NetworkX; run bounded shocks, compare constrained interventions and sensitivity surfaces, and export recomputation-verifiable RiskPacks. Includes 16 scenario-only cases and 11 connector contracts.
[EMNLP main 2026] Provenance Before Prose: Claim-Locked Reporting for Statistical Text Generation
Find which script, notebook, data, command, or AI agent produced a file — locally, with evidence and honest uncertainty.
Explore sleep, training, mood and nutrition together using local records, traceable calculations and optional MCP tools for your preferred AI client.
Evidence-aware multi-engine mathematics runtime for LLMs: exact, symbolic, formal, certified-interval and numeric computation with typed MathIR, trust labels, and full provenance
铃音的记忆写入协议 - an informatics protocol: fragmented, cue-based, symbolic, highly compressed information for AI agents; usable for memory writing and transmission, decodable approximately or via retrieval.
Research artifacts for provenance-bound agent authorization, signed effect evidence, and reproducible security evaluation.
Batch-remove AI provenance and image metadata with ExifTool. CLI + Agent Skill, preserving pixel data.
Find and remove AI provenance signals from files you own: hidden Unicode, token watermarks, visible image marks, and C2PA/EXIF/XMP metadata. Zero-dependency Python 3.10+ core; models, GPUs, and system binaries sit behind opt-in adapters.
Reconstruct scientific frameworks, mechanisms, and flow diagrams as native editable PowerPoint—with provenance-bound, fail-closed QA for Codex.
AI watermark removal built for Apple Silicon. SynthID-class pixel regeneration, visible vendor labels and provenance metadata, with every pipeline decision measured on Metal.