Verifiable Randomness for AI/ML and Simulation

Designed for real-time AI inference and simulation loops. Request and receive verifiable randomness in a single transaction with sub-second latency, scaling to thousands of requests per second.

Deploy your AI agents and simulations across any EVM-compatible chain. Our oracle provides a unified API and consistent security guarantees from Ethereum to Arbitrum, Polygon, and Base.

Built for mission-critical systems with a 99.9% uptime SLA, real-time health checks, automated failover, and detailed audit logs for compliance and model reproducibility.

Ensure deterministic seeding for ML experiments with cryptographically verifiable random inputs. Eliminate result variance across training runs for reliable model comparison and debugging.

Generate tamper-proof randomness for selecting training batches, validation sets, and A/B testing cohorts. Mitigate sampling bias and prevent adversarial manipulation of your data pipeline.

Power agent-based models, Monte Carlo simulations, and synthetic data generation with a high-throughput, low-latency source of entropy. Achieve realistic stochastic environments for accurate risk and scenario analysis.

Integrate a production-ready, API-first randomness oracle in days, not months. Our managed service eliminates the overhead of building and securing your own verifiable random function (VRF).

Provide immutable, on-chain proof for every random value used in published research or financial models. Build trust with stakeholders, regulators, and the academic community through transparent methodology.

Replace expensive, proprietary random number generators with a scalable Web3-native solution. Pay-per-use pricing aligns costs directly with your research throughput, from prototype to large-scale deployment.

Ensure unbiased, reproducible results in training datasets and model validation by seeding processes with verifiable, tamper-proof randomness. Eliminate hidden biases and enable peer review of AI outputs.

Drive complex financial, scientific, and logistical simulations with a robust entropy source. Achieve deterministic replay for debugging and compliance while maintaining true stochastic behavior.

Build transparent loot boxes, random NFT trait generation, and game mechanics where fairness is cryptographically guaranteed on-chain. Build user trust and meet regulatory scrutiny.

Generate cryptographic keys, nonces, and session tokens with entropy backed by decentralized consensus. Mitigate risks associated with weak pseudo-random number generators (PRNGs).

Implement statistically sound user allocation for feature rollouts, canary deployments, and traffic routing. Ensure group assignments are unpredictable and verifiably random.

Facitate transparent DAO proposal ordering, committee selection, and prize lotteries. Replace opaque off-chain draws with a verifiable, community-auditable process.