So Avectic separates the two: AI to understand the work, a deterministic engine to decide it. The same case reaches the same outcome, every time — traceable to the policy behind it. Deterministic intelligence, proven first in prior authorization.
For the first time, machines can read unstructured human work — a note, a chart, a plan — and genuinely understand it. That is a breakthrough. And for the first time, those same machines can give two different answers to the same question. For drafting, that variance is harmless. For a decision governed by policy, subject to audit, and consequential when wrong, it is disqualifying. Intelligence, on its own, is no longer enough.
Machines can finally understand the messy, human input that rules-based software never could. The hardest part of the work — comprehension — is solved.
The same machine can decide differently on identical facts, and quietly change its mind over time. Tolerable for a draft. Unacceptable for a regulated, auditable decision.
Avectic exists for the second half of that sentence. Understanding can be probabilistic. Decisions cannot.
Rigid, reliable, and blind to anything that wasn't already structured.
Fluent, capable, and unable to hold to the same answer twice.
Intelligence was never the hard part.The decision was.
Understanding can be probabilistic. Decisions cannot. So Avectic splits the work in two. AI does what it's extraordinary at — reading and structuring a case in its own words. A deterministic engine does what AI can't be trusted to: apply policy the same way, every time. The understanding is intelligent. The decision is certain.
Hand the whole job to AI agents. Quick to demo — and different every run, opaque under audit, and impossible to certify. For a regulated decision, “usually right” is the liability, not the win.
AI reads and structures. A deterministic engine decides, traceable to the policy behind it. Not 95% of the time — every time.
This is Deterministic Intelligence — the way accountable, policy-governed work gets to use AI at all.
Disconnected systems, formats, and people — none of them speaking the same language.
Every fragment parsed, checked, and aligned against the rules that govern it — deterministic and auditable.
One source of truth, traceable to the policy behind it — with a person in command of the call.
Only structured facts cross the boundary — never the model. The decision is made by rules, not by AI, which is exactly why it reproduces, and why it can be audited and certified. This is the line an end-to-end agentic system cannot draw.
How it works is the easy part to admire.What it changes is the point.
The thesis only matters if the workflow gets shorter. It does — for the coordinator who runs it, and for the patient waiting on the other end.
Same coordinator, same policy — minus the portal-hopping, the re-keying, and the appeal that should never have been necessary. The decision arrives assembled and justified; the person confirms it.
The plan is set. The clinical decision is already made.
Days lost to a back-office bottleneck no one can see.
The surgery moves. The infusion waits. The calendar resets.
An administrative delay becomes a clinical one. This is the cost that compression actually returns.
A stalled authorization doesn't sit still. It moves downstream and multiplies — into capacity that goes unused, revenue that slips, and labor spent chasing what should have cleared the first time.
Six costs from a single delay. Prior Auth LogiQ resolves the authorization at the source — so the cascade never starts.
Avectic has no opinion on what your policy should be. Its one job is to apply the policy you've set, identically on every case, with the criteria and the source revision attached to the result. Fewer malformed submissions. Fewer avoidable appeals. A decision trail that holds up on both sides of the table. Consistency is the product — the policy stays yours.
It's the first place Deterministic Intelligence meets a real, policy-governed, consequential workflow — and holds. Spine and infusion weren't convenient. They were chosen.
If determinism holds under this, it holds anywhere downstream.
Synthetic case shown.
Pilot-ready · synthetic case shown.
Prior authorization is the first proof.It will not be the last.
Strip away the domain and what remains is a deterministic decisioning platform — the part that turns understanding into a decision you can reproduce and defend. Prior authorization is the first application. Spine and infusion are the first proofs. The same engine applies to any decision that is policy-governed, auditable, and consequential when wrong — most of the decisions that matter, in healthcare and well beyond it.
Prior authorization is only the first visible instance of one problem: a decision governed by policy, audited after the fact, costly when wrong. Healthcare is full of the same shape.
Each is the same problem wearing a different name. Deterministic Intelligence is the category that answers all of them.
Policy is evaluated, not estimated. The same case reaches the same outcome, run after run.
Every criterion is checked against a named policy revision, with the source attached to the result.
From input to outcome, the path is recorded — readable by the people who have to stand behind it.
The system explains itself and waits. The decision, and the accountability, stay with your team.
Every decision leaves a record that reconstructs it — what was checked, against which policy, and who signed off.
Illustrative record · synthetic case.
We're opening a small number of pilots. Not a deck marathon — a working session on one of your real, policy-governed workflows, run on synthetic data until you trust it on your own.