The hard questions,
answered plainly.

Those are excellent general-purpose agentic tools: Claude Code helps developers build software, and Cowork helps people carry out knowledge work. They are powerful blank canvases that a skilled person directs, task by task, and the customer owns whatever gets built and its governance.

Supervity Autos are the opposite end of the spectrum: finished, production business applications for specific operations, with the rules, audit trail, learning memory, and cost-optimised models already built in. Rather than vibe-coding a business-critical process from scratch and paying frontier-model rates on every step, a company assembles pre-built Auto blocks and runs a governed operation. The tools help you build; the Auto is the built, governed thing that runs the work.

No. A wrapper is a prompt in front of one model. An Auto is a full stack: pre-built applications, multi-agentic workers, a deterministic rules engine, a living Auto Graph of the business, cost-optimised model routing across providers, and a complete audit trail. The frontier model is one component, called only when a step genuinely needs it.

Many teams can build a demo. Production is the hard part: authority and guardrails that always hold, accountability, learning, cost control, security, and upkeep as the business changes. Assembling that from frameworks, rule engines, knowledge graphs, and observability typically takes an enterprise 18 to 24 months, and still lacks the domain depth an Auto ships with. Supervity delivers it built, governed, and maintained. See the comparison.

On your own cloud, by default. The Auto Graph, the AI Employees, and the audit trail run inside your boundary, so data does not leave the company. Supervity is SOC 2 Type 2 and ISO 27001 certified, and every action is logged and replayable. Details in Control and audit.

You are not locked in. Autos are model-agnostic, using the best of Claude, Gemini, and OpenAI for hard reasoning and Supervity's own small models for the routine, on your own model contracts. If the leading model changes, the Auto can move. See Why Sovereign AI.

Far less than sending every step to a frontier model. By routing most steps to small, tuned models and reserving the large model for hard reasoning, an Auto uses roughly 60% fewer tokens per process. That is what makes running a whole operation affordable. Model it in the ROI Calculator.

No. You set the rules as Auto Policies, which are enforced before any consequential action. High-impact steps wait for a human. Everything is recorded and reviewable. Self-driving does not mean unattended; see Control and audit.

No, and never through a risky big-bang migration. Autos do replace legacy SaaS over time, including the system of record beneath, but they earn their way down the stack rather than forcing it.

The path is transformative but phased. AI Employees start by doing the work on top of the systems already in place, so value arrives in weeks with no disruption. As the Auto Graph becomes the trusted record of how the operation actually runs, the legacy system of record underneath can be retired step by step. You transform the stack from the top down, not by tearing it out.

Autos can replace brittle RPA and take over work priced to headcount, while co-existing with SI partners on complex programs. The direct path to replacing outsourcing spend is AIshore, which targets contracts up for renewal.

Yes. Beyond your own cloud, Autos can run on dedicated hardware in your data center, up to fully air-gapped, through Supervity's infrastructure and cloud partners. This is the Appliance layer of the stack above.

A working Auto on your own data in three weeks, through the AutoPilot Bootcamp. Beyond that, Supervity signs for the outcome through ROI Assurance: agreed AI-first milestones by set dates, and if one is missed, the team keeps working at no additional cost until it is met.