Explore the AI lifecycle before you sign in.

Build AI models, AI applications and production systems with one lifecycle for repositories, evidence, benchmarks, GPU work, deployment and governance.

Plan and govern native AI or foundation-model development from corpus and tokenizer work through checkpoints, provenance, evaluation, release and deployment.

Organize AI model training, fine-tuning, checkpoints, GPU jobs, datasets, costs, telemetry and evidence in one governed workflow.

Plan and govern rentable GPU capacity for AI training, evaluation and inference with provider connections, job lifecycle, metering and cost controls.

Manage AI datasets, corpus revisions, metadata, storage, provenance and downstream impact alongside the models and training runs that use them.

Version AI source, models, checkpoints and datasets with real Git plus encrypted content-addressed storage, semantic artifact indexing and signed repository history.

Build signed AI provenance graphs linking repositories, revisions, Git, CAS, datasets, environments, checkpoints, benchmarks, verification and releases.

Verify AI artifacts against current evidence, issue signed verification receipts and govern Trust Passports without converting self-claims into approval.

Run reproducible AI benchmarks against immutable revisions with case-level evidence, signed results, worker execution and currentness checks.

Deploy evidence-bound AI endpoints with provider-owned lifecycle, signed manifests, preview and production gates, health checks and rollback-aware control.

Publish, buy and license AI assets with server-derived pricing and rights, wallet settlement controls, entitlement issuance, refunds and creator payout workflows.

Operate private AI projects with OIDC/SAML SSO, role provisioning, server-enforced governance, provider secret references and signed webhook integrations.

Apply server-side AI lifecycle policies, human approval gates, audit history, cost controls and fail-closed evidence rules across training, release and deployment.

Turn an AI startup idea into a structured project covering architecture, model choices, datasets, GPU work, verification, deployment, wallet and product delivery.

Understand how a Zippri AI Trust Passport can summarize approved verification scopes while remaining tied to current signed evidence and revocation state.

Plain-language definitions for AI provenance, model registry, checkpoints, CAS, benchmarking, verification, GPU cloud, deployment, SSO, webhooks and AI governance.

Explore Agastya Research Factory R2: continuous frontier, civilization, robotics, affective and program-gap research with evidence, critic verification, knowledge scoring and human-gated training.

Turn evidence-backed AI research tools into trusted prototypes, tests, verified packages, immutable repository artifacts and controlled Marketplace drafts.