Audience
AI developers, organizations, and data contributors looking for a tool to build or access specialized LLMs using privacy-preserving data contributions and decentralized model governance
About Decide AI
DecideAI is a decentralized AI ecosystem built around three core components that offer a framework for privacy-preserving data sharing, annotation, model training, and continuous improvement using techniques like RLHF and DPO. Decide ID is a zero-knowledge proof-based identity system that verifies contributors’ authenticity and reputation while preserving privacy through techniques like 3D face scans and liveness checks. Decide Cortex provides access to specialized, high-quality LLMs and curated datasets generated through the protocol, enabling clients and developers to adopt or tailor models without starting from scratch. The platform is designed to support secure, verifiable contributions of proprietary or domain-specific data, incentivize long-term participation via its native DCD token, and reduce reliance on large centralized AI providers by enabling on-chain or hybrid model hosting.
Other Popular Alternatives & Related Software
Twine AI
Twine AI offers tailored speech, image, and video data collection and annotation services, including off‑the‑shelf and custom datasets, for training and fine‑tuning AI/ML models. It offers audio (voice recordings, transcription across 163+ languages and dialects), image and video (biometrics, object/scene detection, drone/satellite feeds), text, and synthetic data. Leveraging a vetted global crowd of 400,000–500,000 contributors, Twine ensures ethical, consent‑based collection and bias reduction with ISO 27001-level security and GDPR compliance. Projects are managed end‑to‑end through technical scoping, proofs of concept, and full delivery supported by dedicated project managers, version control, QA workflows, and secure payments across 190+ countries. Its service includes humans‑in‑the‑loop annotation, RLHF techniques, dataset versioning, audit trails, and full dataset management, enabling scalable, context‑rich training data for advanced computer vision.
Learn more
Findora
Deploy financial infrastructures with privacy-preserving transparency. Findora enables assets of any nature - dollar, bitcoin, equity, debt and derivatives. Its mission is to address the challenges necessary to support this broad class of assets and diverse financial use cases, providing confidentiality while retaining the transparency of other blockchains. Findora uses zero-knowledge proofs and secure multi-party computation to support many privacy-preserving features. Specialized zero-knowledge proofs allow Findora to be publicly audited, while data remains confidential. Findora features a high-throughput ledger design, and reduces storage requirements through cryptographic accumulators. Findora breaks open data silos for easy interoperability between the main- and side-ledgers. Findora provides you with the tools, documentation, and support to help you build your applications. Develop privacy-preserving applications on the Findora testnet today.
Learn more
OORT DataHub
Data Collection and Labeling for AI Innovation.
Transform your AI development with our decentralized platform that connects you to worldwide data contributors. We combine global crowdsourcing with blockchain verification to deliver diverse, traceable datasets.
Global Network: Ensure AI models are trained on data that reflects diverse perspectives, reducing bias, and enhancing inclusivity.
Distributed and Transparent: Every piece of data is timestamped for provenance stored securely stored in the OORT cloud , and verified for integrity, creating a trustless ecosystem.
Ethical and Responsible AI Development: Ensure contributors retain autonomy with data ownership while making their data available for AI innovation in a transparent, fair, and secure environment
Quality Assured: Human verification ensures data meets rigorous standards
Access diverse data at scale. Verify data integrity. Get human-validated datasets for AI. Reduce costs while maintaining quality. Scale globally.
Learn more
Flower
Flower is an open source federated learning framework designed to simplify the development and deployment of machine learning models across decentralized data sources. It enables training on data located on devices or servers without transferring the data itself, thereby enhancing privacy and reducing bandwidth usage. Flower supports a wide range of machine learning frameworks, including PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and XGBoost, and is compatible with various platforms and cloud services like AWS, GCP, and Azure. It offers flexibility through customizable strategies and supports both horizontal and vertical federated learning scenarios. Flower's architecture allows for scalable experiments, with the capability to handle workloads involving tens of millions of clients. It also provides built-in support for privacy-preserving techniques like differential privacy and secure aggregation.
Learn more
Pricing
Free Trial:
Free Trial available.
Integrations
API:
Yes, Decide AI offers API access
No integrations listed.
Company Information
Decide AI
Founded: 2021
United States
decideai.xyz/
Videos and Screen Captures
Other Useful Business Software
MongoDB Atlas runs apps anywhere
MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
Product Details
Platforms Supported
Cloud
Training
Documentation
Support
Online
