Eleven focused products.
One platform.

Log in, get a governed Kubernetes workspace. No kubectl, no tickets.

On first SSO login every user gets an isolated namespace with quotas, default-deny networking, storage, and a web terminal — provisioned automatically, reconciled continuously.

Jupyter or VS Code on a GPU in seconds. Idle environments shut themselves down.

Single-click Jupyter, Marimo, Streamlit, Gradio, and VS Code environments — GPU-ready, isolated per user behind a per-pod auth proxy, with SSH access and idle shutdown by default.

Admins write the template. Users fill a form. Kubernetes runs the job.

Self-describing training templates render straight into UI forms — with live quota checks, streaming logs, parsed progress bars, and one-click TensorBoard.

Your own Hugging Face Hub. Change one env var — every client just works.

A self-hosted, HF-compatible model and dataset registry: transformers, datasets, huggingface-cli, and git-lfs work unchanged — plus a browsable Hub UI with model cards, file viewer, and commit history, OIDC, audit, quotas, and pull-through caching of the public Hub.

OpenAI- and Anthropic-compatible inference on your GPUs — measured to the token.

A self-hosted Model-as-a-Service: an OpenAI- and Anthropic-compatible gateway that now also serves embeddings, reranking, audio (TTS and ASR), and vision — with KServe deployment management, multi-deployment routing with circuit breakers, and per-user, per-key, per-model cost attribution.

An OCI registry with real identity, runtime-mutable policy, and an air-gap story.

A curated fork of CNCF Zot: single binary, modern admin UI, OIDC SSO, access policies you edit at runtime, namespace quotas, robot accounts for CI — deployable on Kubernetes, air-gapped, or bare metal.

Agents as a first-class Kubernetes primitive — versioned, sandboxed, fully traced.

Author a versioned Agent, then run it as Sessions — autonomous tasks or interactive chat — on Kubernetes. Per-session sandbox isolation with deny-by-default egress, built-in / MCP / custom tools, cross-session memory, cron schedules, always-on services, and a live event trace with token accounting — behind an OIDC SSO front door with per-user sessions. All reconciled from CRDs on agent.tensorstack.dev.

Ground your agents in your documents — scanned PDFs included, every answer cited to the page.

The knowledge layer for TAIP agents: ingest a document corpus — scanned PDFs included — and serve it back as hybrid, reranked, page-cited retrieval. Multiple isolated knowledge bases behind OIDC SSO and per-KB access control; embeddings and reranking on your own InferX, vectors in a pluggable vector DB. Agents call mcp__kb__search and cite the page instead of guessing.

Your Slurm scripts, unchanged — running on Kubernetes, with one login, one home, one quota.

A real, multi-tenant Slurm 25.11 cluster on Kubernetes. Researchers run their existing sbatch / srun / sacct workflows byte-for-byte unchanged; the platform supplies one identity, one shared /home and /scratch, and one quota — and operators run Kubernetes instead of a separate HPC island.

Bare hosts to a working AI platform — even with the internet unplugged.

An air-gap-first platform installer: Kubernetes, eBPF networking, replicated storage, identity, registry, and GPU operators — packed once on a build host, deployed anywhere, idempotently.