SAPTIVA Studio is the control plane: where your organization builds, operates and governs its AI. It turns scattered context into agents and workflows, routes each workload by residency, latency and cost, logs every decision and meters every cost.
Cloud, hybrid, on-premise or air-gapped, under one control plane. From Mexico, built for the world.
One sealed decision, replayed frame by frame: the workload arrives, the configuration is read, the route is locked, it runs in the environment the customer configured, and the record is sealed.
Same routing, audit and cost at every level.
Define an agent in Studio. It runs.
Bring your own compute. Studio routes, records and meters.
Your cluster, your GPUs, the same audit trail.
Where your organization builds, operates and governs all of it: agents, workflows and an AI Lab on your data. Savant, RAGster and Dictaminador are how it ships. In production in weeks.
The orchestrator inside Studio. Places every workload across cloud, on-prem, hybrid and air-gapped. Not sold separately.
Deployment modes and the security posture go deeper on their own pages: Deploy Anywhere → · Security & Compliance →. Both are what Studio does, not separate products.
Every workload is placed by the same three signals before it executes. The route is not a default someone set once. It is recomputed per request, and the reasoning is logged.
Every engagement ships with a structured enablement program. Run inside your organization. Your team gets autonomous on what we deployed.
Every module maps to a specific capability you deployed. Your team learns to operate, extend, and audit the applications without us. Autonomy is the exit criterion.
New module each cycle. Enablement closes in weeks, not the months enterprise software procurement takes. Each module opens the next use case.
If the only reason you still need SAPTIVA AI is that your team can't operate the platform, we haven't delivered. Enablement is how dependency becomes capability.
ACMES's team operates and audits their own workflows. Ibero's faculty extends their own Studio apps. The exit criterion isn't training completed. It's capability owned.
Every architectural decision traces back to one of these. Our customers cannot afford for them to be otherwise.
Set once per data class, applied on every route. Your data runs in the environment you chose for it. Residency is architectural, not administrative.
You choose the model, the cloud, the deployment mode. Swap the LLM and Studio routes around it. Change the cloud and the record still holds. If we can only keep you by trapping you, we haven't earned the relationship.
Every routing decision, every execution produces an immutable record: readable, exportable, signed. If something goes wrong, you can prove what the platform did and why.
Production from day one. Our embedded engineers land inside your team, ship the first use case in two weeks, and stay until it runs. We optimize for what still runs eighteen months later.
In production at Rappi, Banco Invex, MultiMoney, Universidad Iberoamericana, and ACMES. KAL, the first open-weight Mexican LLM, built by SAPTIVA AI, runs on it as a selectable model.
If you're evaluating AI infrastructure for your enterprise and want to go below the overview, our engineering team responds within 48 hours. Not a sales sequence.