AI Consulting in Cleveland

Every health system engagement starts with a signed HIPAA Business Associate Agreement before any system access changes hands. From there, we route clinical and administrative data exclusively through model endpoints with contractual zero-retention terms — the major enterprise tiers from Anthropic, OpenAI, and Azure OpenAI all qualify, and the signed data processing agreement goes into the engagement file. Access is scoped at the minimum: if the workflow is automating prior authorization follow-up, it gets read access to the specific patient status fields it needs and nothing else. We don't route PHI through consumer-grade APIs, we don't store patient data outside the health system's approved infrastructure, and every data flow is documented in writing before any credential is issued. If a health system's IT security team wants to review the architecture, that review happens before go-live — not after.

Yes, and the ERP integration question is usually the first thing we map in the audit. For SAP, Oracle, and the mid-market ERPs common in Northeast Ohio manufacturing — Epicor, Infor, SYSPRO — we build through the official API or database layer depending on what the system exposes. The automation reads the source data, applies whatever transformation the workflow needs (formatting a purchase order for a supplier portal, generating a compliance summary for a quality audit, flagging a variance for the operations manager), and writes the output to the destination. We don't build brittle screen-scraping solutions that break on the next UI update. If your system has an API, we use it. If it doesn't, we work with your IT team to establish a controlled data extract. Chemical manufacturers with process safety or EPA reporting requirements get the same documentation discipline: every data flow mapped, every output logged, every change to the automation versioned and reviewed.

The highest-leverage starting points we see for financial services firms in this market — regional banks, investment advisors, insurance intermediaries — tend to cluster around three problems. First, client onboarding: the back-and-forth document collection, KYC checklist completion, and account setup steps that take two weeks when they should take two days. An automation that sends the right document requests, tracks completions, and notifies the relationship manager when the file is ready cuts that cycle substantially. Second, internal knowledge: compliance procedures, product guidelines, and regulatory updates that live in PDFs on a shared drive and take new hires months to internalize. A knowledge assistant built on your actual documents — not a generic chatbot — answers those questions in seconds. Third, reporting: the weekly or monthly snapshots that someone pulls from multiple systems and assembles into a summary for management. That's an automation, not a human job. Ohio Department of Commerce regulatory requirements for licensed entities are a real consideration, and we build with audit trails and role-based access as defaults, not afterthoughts.

For a single, well-scoped workflow — one integration, one output, one team using it — the build runs two to four weeks from signed scope to go-live. The front end of that timeline is the scoping work: understanding exactly what data moves where, what the edge cases are, and what done looks like. That scoping usually happens in a $497 Founder Review Call if the business hasn't done an audit, or it's already mapped if they came through the $99 AI readiness audit first. The audit is genuinely the faster path: it surfaces the highest-leverage workflow, documents the current state, and gives the engineering team a clean brief to build from. Businesses that skip scoping and go straight to 'build something' tend to end up with a two-week build that takes eight weeks because the requirements keep shifting. We'd rather spend the first week getting the spec right than spend the last four weeks reworking a half-finished build.

Yes. Law firms, accounting practices, commercial real estate firms, and staffing companies across the Cleveland metro are all running workflows that automation handles well — intake screening, document summarization, client communication follow-up, internal knowledge retrieval, proposal generation. The compliance requirements differ from healthcare and manufacturing, but the underlying pattern is the same: a human is doing repetitive, rules-based work that takes time away from the higher-judgment tasks the business actually needs them for. The $99 AI readiness audit is the right starting point for any professional services firm that isn't sure where to begin. It maps the current workflows, identifies where the friction is highest, and produces a prioritized list of automation candidates — not a vendor pitch deck, an operational document the leadership team can act on.