Workflow clarity
Show us where the work really happens.
We inspect the messy middle: spreadsheets, docs, internal tools, support queues, handoffs, and the shadow AI usage that never made it into an architecture diagram.
AI Strategy Consultation
Find the AI work that should be automated, governed, or left alone.
Prosper Logic consults on the workflows, model choices, data handoffs, and product surfaces where AI is already affecting your business. You leave with a prioritized map of what to build, what to stop, and what needs guardrails before it scales.
01 / Map
Where AI is already touching revenue, risk, and delivery.
We trace the real workflow, not the slideware version: tools, handoffs, prompts, approvals, customer-facing surfaces, and internal ownership.
02 / Stress test
Where quality breaks when volume, ambiguity, or compliance pressure rises.
The audit looks for silent failure modes: missing review gates, weak data boundaries, brittle prompts, unclear fallback paths, and vendor lock-in.
03 / Roadmap
A build sequence your team can actually execute.
You get a ranked action plan, from fast operational fixes to deeper systems work that belongs in a product or consulting engagement.
Model risk
Separate useful automation from fragile theater.
We pressure-test the parts of your system where hallucination, stale context, permissions, or vague ownership could turn a helpful workflow into a liability.
Commercial path
Turn the audit into a decision, not a report.
The output is a priority order: immediate fixes, high-leverage builds, tooling changes, and the work that should wait until the system is ready.
Start the intake
Tell us what you are trying to make reliable.
The form stays public so there is no signup wall. If you happen to be signed in, Clerk can prefill your name and email and Convex will attach the request to your user row.
We reply personally within two business days from hello@prosperlogic.ai.
Submissions are stored in Convex before notification email fan-out, so the request is durable even if email delivery is skipped.
No drip sequence. No automated sales handoff. Just enough context for a useful first response.
Proof model
Named testimonials will wait until the work is approved to publish.
Until then, the page shows the operating standard behind the audit: specific evidence, explicit tradeoffs, and a roadmap that can survive contact with delivery work.
Evidence first
Decisions are tied to artifacts.
We ask for the workflows, docs, tools, and examples that reveal how AI is actually being used, then mark what is known, inferred, or unverified.
Risk register
Fragility gets named early.
The audit calls out brittle prompts, unclear ownership, weak data boundaries, missing approvals, and vendor assumptions before they become expensive.
Build path
Recommendations come sequenced.
You get the next move, the later move, and the work we would explicitly avoid until the business case or system maturity is stronger.