Tensile is the enterprise-grade control plane for training, inference, and agents. Work routes straight onto your own clusters and clouds, or into a state-of-the-art sandbox when it needs isolation — and every run comes back verified. Stop solving infrastructure and platform-engineering problems; focus on what's important.
Every serious AI team rents public cloud by the second, then hires an infra team to spend months rebuilding the same stack every other company is building too — scheduler, sandboxes, eval harness, dashboards. It's undifferentiated plumbing. Tensile is that stack, already built and wired together, running on your own hardware.
Run every workload on hardware you already own. Nothing leaves your perimeter, and there's no per-second vendor meter running while you iterate.
Scheduler, sandboxes, eval harness, observability — the plane every company reinvents, already built, wired together, and enterprise-grade.
Point your best engineers at models and agents, not at YAML, Terraform, VPC rules, and a metrics stack. Your team stays AI-native; we manage everything below.
The whole surface is small on purpose: a few nouns you work with — agents, models, data, evals — the verbs you run on them, and the primitives we guarantee underneath. You live in the nouns and verbs; the primitives are our job.
Train agents and models with checkpoints and direct data integration, gang-scheduled onto your clusters.
Optimize for inference speed and ship inference deployments — load-tested before you commit the compute.
Ship production agent deployments, leveraging state-of-the-art sandboxes when a run needs isolation.
Store your data and models, versioned and ready to use across every workload.
Tensile Sandbox is state-of-the-art Firecracker microVM isolation — sub-second boots, one VM per run, on your own hardware. A drop-in replacement for Daytona, Modal, and E2B that runs ~3× cheaper per run at scale (up to ~6× on bursty workloads, and effectively $0 on startup credits). One sandbox carries a workload from first agent run to production — the same substrate for agents, evals, RL rollouts, and load tests. Training and heavy inference skip the sandbox and schedule straight onto your GPU clusters.
Cold-start a fresh microVM per run — no warm pools to babysit.
Kernel-level isolation per tenant and per run, not shared containers.
Packing many sandboxes per node beats per-second SaaS pricing — free on startup credits.
Run it on your own infra, or let us manage the whole thing for you.
AI work isn't one job. Different teams need different parts of the stack — Tensile gives each the surface it needs, without forcing anyone into someone else's tooling.
Right-size cluster capacity, set autoscaling policies built for the team, and keep cost and reliability in check. The workload engine load-tests demand up front, so you're never over- or under-provisioned.
Ship agents and inference to production — sandboxed when it matters, scaled automatically, and verified against your SLOs.
Train and post-train models on your clusters with checkpoints and direct data integration. SFT, RL, DPO, LoRA — your frameworks.
You used to choose: build your own stack for control and low run-costs, or buy a managed one for speed and a clean experience. Tensile gives you both — build-like run costs with a buy-like experience — on infrastructure you already own.
You pay for your own compute, not a per-second SaaS markup. Our sandbox engine packs many workloads onto each node, so at scale it runs ~3× cheaper per run than Daytona, Modal, or E2B — up to ~6× on bursty workloads, and effectively $0 while startup credits last.
No platform team, no YAML archaeology. Connect your cluster or cloud, submit a workload, get a verified result. We manage the clouds, VPCs, containers, scheduling, and autoscaling underneath.
The same sandbox carries a workload from first agent run to production — sub-second boots, hard isolation, packed many-to-a-node. One substrate for agents, evals, RL rollouts, and load tests.
GPUs anywhere — hyperscaler, neocloud, Slurm, or on-prem. Tensile brings the same contract and state-of-the-art execution to whatever compute you already run. Use any backend and any library inside the platform, and adopt a single surface as a tool in your chain or run the whole platform end to end — it's configurable either way, so you don't change what isn't broken.
The primitives every workload needs, provided across the whole plane so you never build them yourself.
Tokens, CPU, and GPU hours rolled up per workload, team, and substrate.
Live events, cost, latency, and span-tree debugging — no metrics stack to run.
Checkpointing, retries, and replayable runs so failures don't lose work.
OIDC SSO, per-tenant isolation, and an append-only audit trail on your infra.
We run our own agents, training, and evals on Tensile every day — the same plane we're opening to you. Frontier research agents ship in the product; fork them or bring your own.
Point Tensile at the compute you already run — connect, submit a workload, get a verified result. No platform team required. In early access today; request access and we'll get you running on your own hardware.
# Install the SDK + CLI, then register your cluster or cloud pip install tensile tensile connect # → K8s / Slurm / GCP / AWS / Azure / Nebius
# Declare training, inference, an agent, or an eval tensile run train.yaml tensile logs --follow # → verified outcome + cost, streamed back