Your context becomes intelligence.
It runs where you decide.
Every decision provable.
AI value stuck outside your P&L.
A stalled pilot is a paid line item with nothing on the other side. Your context is scattered: documents, databases, systems, and a pilot on each that never shipped. Bring it. SAPTIVA Studio brings it together inside your perimeter, your teams put it to work as agents and workflows, and every decision is signed. The value lands on your P&L.
Bring the pilot that never reached production.
Our engineers and yours rebuild that pilot as a working process on your own data, fitted to how your team already works. What you build next in Studio runs on the same control plane as the first one. Nothing starts from zero again.
Start a five-day Discovery → An engineer, not a rep, replies within 48 hours.SAPTIVA Studio, live. Every row is a signed decision: which model, which environment, what it cost, what came back.
Each one began with hardware nobody could run, work done by hand, or 3 weeks for every answer.
Savant, the industry advisor, inside SAPTIVA Studio: consumer-book risk across the banking system, answered inside the bank’s perimeter.
Risk data, regulation and the bank’s own book never lived in the same place. Every answer meant an analyst, 3 weeks, and a spreadsheet no auditor could trace.
Asked once, inside the perimeter, answered with sources attached. Savant, the industry advisor, in production in two weeks.
The lab’s GPU panel in SAPTIVA Studio: one node, eight GPUs, 759.8 GB of capacity, reserved versus available per card, and the models running on each.
A new engineering program needed a serious AI lab, on-premises, without hiring a platform team or renting the cloud. The hardware sat idle. Research stayed on laptops.
SAPTIVA Studio on their cluster, eight funded projects running, faculty trained. Three months from powered-on hardware to researchers in production.
Marketing Core, results view: thirty days of mail planning per microzone. Delivered, opened and clicked per campaign, against the prior period.
Promos and partners change from one neighbourhood to the next, but every email was built by hand. One zone got one email every two weeks. The rest of the city heard nothing.
Marketing Core picks partners and promos per microzone, generates image and copy, builds the email on the team’s template and publishes it, all on the client’s own infrastructure. One month to the first real send.
Dictaminador, the ruling workflow in SAPTIVA Studio: read, filter, validate against the criteria, sign the verdict into the record.
Verification and rulings ran manually: slow, uneven between analysts. When a carrier or an auditor asked why a file was approved, the answer was somebody’s memory.
Dictaminador ships the ruling: documents verified, judged against the broker’s own criteria, every decision signed into the record. Two weeks to production.
Swap the model. Change the cloud. Change the country. Zero lock-in.
Where your organization builds, runs and governs all of it: agents, workflows and an AI Lab on your data. Savant, RAGster and Dictaminador ship here. In production in weeks.
See what ships in Studio →Studio decides where each workload runs and writes a signed record: which model, which environment, what it cost, what came back. Nobody sits at it. It runs whether you are watching or not.
See how routing works →
The model will change.
The switch stays yours.
Models are the part that changes. Studio is the part that does not: where it runs, what it costs, and the proof of every decision stay under your control. Three ways in, one control plane - the same routing, audit and cost at every level.
Every routing decision and model output is written to an immutable trail your auditor can read without a data request.
Sample records. After an edit, the new fingerprint is computed in your browser.
The obstacles standing between your teams and the value AI can deliver. Every business faces them. Three mandates decide: the business, technology and compliance. Four desks hold them, and one platform answers all four.
Same platform, same experience, whichever environment you require. When the rules change, you do not replatform.
AWS, Azure, GCP, OCI. Private. Multi-region.
Your datacenter. Your hardware. Your perimeter.
Zero external connectivity. Sealed.
Sensitive workloads inside. Burst to cloud. One control plane across both.
Control is not where your datacenters are. It is who holds the switch.
Your stack, your keys →of enterprise AI pilots never reach the P&L. Most fail because the tools do not learn or fit the daily workflow.
of workloads will move from global to local providers. Every move is a routing decision.
Savant in production inside the bank's own perimeter.
You will not buy your AI. You will own it. It runs inside your perimeter, and it keeps running if we disappear.
SAPTIVA AI sits outside the perimeter, drawn dashed. If we disappear, it keeps running.
“Model selection, routing and where inference runs become an ongoing operating discipline, not a one-time choice.”
Fragmented environments and tools cannot decide where a request runs when a prompt, agent, or tool-call reaches a model. Studio does.
Every environment, every model, every tool.
One control plane, one signed record, two weeks.
One layer between everything that calls a model and everywhere a model can run. It decides where each request runs, under the configuration you set, and signs the record. That layer is SAPTIVA Studio.
Read the full explainer →Which model, which environment, what it cost, what came back. Signed.
Cloud · On-premises · Air-gapped · Hybrid. One control plane across all four.
Per workload, per request. Your configuration, your keys. Nobody sits at it.
Append-only trail your auditor reads without a data request.
UNDER THE HOOD: frIdA, THE ORCHESTRATOR INSIDE STUDIO. FOR TECHNICAL READERS →
Built for enterprises with 1,000 or more people, or $100M or more in revenue, with a technology team of their own.
Bring the one thing you cannot get into production. We build it on your data, inside your perimeter, in Studio. You leave with a signed record of every decision it made.
Or start with a bootcamp: your team, on the platform, with your data.