Legacy SaaS
More software. More people.
AI assists, but people still operate screens, queues, and workflows.
Ceiling
Most enterprises already rely on some mix of business software, agent-building tools, systems integrators, and outsourcing. Each can move work forward. Each also caps out. Supervity Autos are built for the next ceiling: software that completes the work while people stay in command.
AI assists, but people still operate screens, queues, and workflows.
The enterprise still assembles authority, safety, memory, and model economics.
Consultants ship the project; the customer keeps the maintenance burden.
Labor arbitrage lowers cost, but the work still scales with people.
A governed operating model that finishes the work and compounds every cycle.
The difference is not another feature list. It is who does the work, where data lives, how value arrives, and who is accountable for the outcome.
| Legacy SaaS | Agent platforms | Systems integrators | BPO / outsourcing | Supervity Autos | |
|---|---|---|---|---|---|
| Who does the work | Your people, using screens | Agents your engineers build | The SI's consultants | An offshore team | AI Employees, supervised by your people |
| What you pay for | Seats and modules | Tools, plus build and upkeep | Hours and projects | Headcount | Outcomes, priced to value |
| Data control | Vendor cloud | Varies; you assemble it | Leaves to a third party | Leaves to a third party | Stays on your own cloud |
| Time to first value | Months to configure | Months of engineering | Quarters | Quarters to transition | A working Auto in 3 weeks |
| Improves over time | On the vendor's roadmap | Only if you keep building | Ends when the project ends | Capped by labor rates | Compounds via the Auto Graph |
| Accountable for the result | No | No | For the project, not the outcome | For staffing, not the outcome | Yes, through ROI Assurance |
Comparison describes typical category characteristics, not any single named product.
Each category solves a real problem. Each also hits a different ceiling—people, engineering, maintenance debt, or labor arbitrage. The difference with Supervity is that the operating model itself changes.
Traditional business software was designed around a human at a screen, with AI added on as an assistant.
Each new tool is another silo to log into and staff, so the operating load stays with people.
An Auto starts by doing the work across those systems, then can replace the system of record step by step rather than through a rip-and-replace.
Agent-building platforms hand engineering teams the model calls, tools, and memory and ask them to assemble the rest.
The enterprise still owns authority, safety, auditability, upkeep, and high model spend on every step.
Supervity ships the governed operation already assembled—Auto Apps, enforced rules, full audit trail, and cost-optimised models. Building the equivalent typically takes 18 to 24 months. See the FAQ.
An SI engagement ships hours and ends with a custom system that the customer then owns and maintains.
The project ends, but the customer keeps the integration complexity and maintenance burden.
Each phase leaves more of the operation running on a platform that keeps improving, and Supervity signs for the outcome. For complex programs it can co-deliver with SI partners. The direct replacement path is AIshore.
Outsourcing moves work to lower-cost people, so savings are tied to labor rather than to a new operating model.
The savings stop where wages stop, while the data and know-how still leave the building.
AIshore does the work with AI Employees on the customer’s own systems, cutting cost on day one and compounding from there without surrendering control.
The large AI models from Anthropic, Google, and OpenAI are extraordinary, and Supervity uses them. The question for an enterprise is not which model to bet on, but who turns models into governed, affordable operations that run on the company's own terms. That is the Auto. Read Why Sovereign AI for why depending on a single model is a risk worth avoiding.
Anthropic · Google · OpenAI and the best available models.
Authority, rules, cost controls, traceability and model choice.
A governed operation that acts across your systems and stays under human command.
Work completed, value measured, and the operating graph deepened every cycle.
Pick one job, and Supervity will stand up a working Auto on your data in three weeks so the comparison is real.
The work runs itself. People stay in command.