Epismo OS
Freemium
Teams using multiple AI tools on the same tasks
The founder becomes the bottleneck not because they hoard decisions, but because the judgment behind those decisions was never written down — so every edge case routes back to them anyway. Supanova exists to capture that judgment and make it repeatable without removing the human from consequential calls.
Supanova builds managed AI workflows for owner-led service businesses, starting with a scoped engagement that maps real decision logic — not the three-box diagram on the whiteboard, but the hundred micro-decisions inside it. The EchoBend case the vendor documents shows 14 combined staff-hours of daily accounting and filing work running automatically, with 412 checks protecting each handoff and a human called in only when the system hits an unapproved boundary. The Alvarado prototype shows proposal time dropping from 11 days to 3, with the contractor reviewing and approving every material decision before it moves. Where it breaks: the approach is deliberately bounded, so teams expecting broad platform transformation or undefined integrations will find that outside the stated scope. The entry point is a paid engagement — no free tier exists.
Bottom line: Pick this if you run a service business where founder judgment is the ceiling and you need one workflow made safe and scalable with evidence behind every run; look elsewhere if you need an off-the-shelf SaaS tool you can configure without a managed engagement.
30-day baseline, guarded workflow, and evidence-backed next step
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Freemium
Teams using multiple AI tools on the same tasks
Paid
E-commerce and retail businesses
Supanova builds managed AI workflows by first mapping what actually happens inside a process — not the stated workflow, but the exceptions, edge cases, and judgment calls that live in a few heads and never made it into a checklist. The core method moves through five stages the vendor labels Observe, Bound, Build, Prove, and Operate: find what already works, set the authority limits, encode the pattern, measure the result, then compound from there. Human checkpoints are not optional — they are structural. Every run leaves inspectable evidence so the team can trace what the system decided, what it held for human review, and why.
The differentiating feature is the guardrail architecture. Rather than autonomous execution, Supanova workflows are designed to stop at boundaries the client sets and hold work until a human decides what should exist next. The EchoBend engagement the vendor documents shows this concretely: when a filing location is not found in the approved registry, the system holds the file — nothing is misfiled — and the next run resumes from the decision the human made. The vendor calls this ‘evidence-backed’ operation; in practice it means every exception is logged and attributable, not silently swallowed or incorrectly handled.
Supanova targets owner-led businesses in the $10M–$50M range where scaling through hiring alone has started to break down. It fits teams where the problem is not missing software but missing replicable judgment — proposal generation, routine finance and filing, client intake decisions. It does not fit teams looking for a self-serve platform, a free prototype environment, or broad transformation across undefined integrations. The Proof Month entry structure means teams commit to a paid engagement before seeing a working system, which is the right call for a vendor that promises real inputs and real exceptions — and a hard stop for teams without budget approval for that first step.
No API is available and no self-hosted option exists. The vendor states that data, outputs, and confidential work remain the client’s. Integration scope is defined per engagement; undefined integrations are explicitly listed as outside the Proof Month deliverable.
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