AI Consulting in Greenville

Yes. SAP and Plex are the two most common ERP environments we encounter in Greenville-area manufacturing supplier builds. For SAP, we integrate through standard RFC or BAPI calls depending on what the instance exposes, or through SAP's API Hub if the firm is on S/4HANA with OData services enabled. For Plex, the Smart Manufacturing Platform has a REST API we connect to for production order status, supplier scorecards, and quality records. The integration approach depends on what your IT team has locked down — some tier-two suppliers run on-prem SAP with firewall restrictions that require an on-site connector agent rather than a direct cloud-to-cloud call. We scope the integration architecture in the audit phase before any build starts, so there are no surprises about what's technically reachable. The goal is usually a one-way or two-way data sync that replaces a manual export-import loop someone is currently doing by hand every shift or every morning.

Every healthcare build starts with a signed Business Associate Agreement before any PHI is in scope. That's not a checkbox — it defines the data boundary for the entire engagement. On the model side, we route any workflow that touches patient data through enterprise API endpoints with contractual zero-retention and no-training terms, typically Azure OpenAI or Anthropic's enterprise tier, where the signed DPA is part of the service agreement and prompts are not retained beyond the request lifecycle. Access is scoped to the minimum necessary fields — if a prior auth status workflow only needs claim ID, payer, and status code, it never sees name or date of birth. We map every data flow on paper before credentials change hands, and the compliance officer or privacy team at the health system reviews and signs off on the data flow diagram before go-live. Builds touching clinical documentation add a human-in-the-loop gate so no AI-generated clinical text reaches a patient record without licensed review. We don't shortcut any of this for speed — a HIPAA breach at a regional health system is an operational and reputational event that no efficiency gain justifies.

If the supplier handles technical data covered by the United States Munitions List — drawings, specifications, process documents for defense-related aerospace components — then yes, ITAR applies and it shapes the build architecture from the start. The core constraint is that ITAR-controlled technical data cannot be processed by foreign nationals or transmitted outside the United States without a license or applicable exemption. For AI workflow builds, that means the model processing layer must run on infrastructure that is both US-based and ITAR-compliant. Azure Government and AWS GovCloud both offer ITAR-scoped environments with appropriate data residency guarantees. On-prem deployment inside the supplier's facility is also an option for firms that need the tightest control. We don't deploy ITAR-controlled data to standard commercial cloud endpoints regardless of where the servers are physically located, because cloud platform employee access policies don't satisfy the nationality control requirement.

The most common entry point for services firms in the Greenville market is internal knowledge and onboarding. If your firm has grown past fifteen to twenty people, you almost certainly have critical process knowledge that lives in the heads of two or three senior people — how to handle a particular client escalation, where to find the non-obvious clause in your standard contract, what the actual steps are when a project goes sideways. When one of those people leaves or is out, the rest of the team either slows down or makes it up. A knowledge assistant build captures that institutional knowledge in a structured, searchable form that a new hire or junior employee can query in plain language. The second common starting point is sales and proposal operations — specifically the gap between a qualified lead and a proposal that goes out the door. If that step involves a senior person pulling from five different sources to build a custom document, it's automatable. The $99 audit is the fastest way to figure out which of these is costing your firm the most right now, because the answer varies by how the firm is structured and what growth stage you're at.

Most first builds ship in two to four weeks from signed scope to production handoff. The audit takes about a week — we review your current workflows, map the data flows, and identify the two or three highest-leverage automation candidates. From there, if you approve a build, the scoping call and technical requirements take another two to three days. The build itself is typically two to three weeks depending on the integration complexity: a straightforward workflow with a single ERP or practice management connection is on the shorter end; a build that bridges two systems with non-standard APIs or requires an on-prem connector agent runs closer to four weeks. We don't compress timelines by skipping the integration architecture review — that's how you end up with something that works in QA and breaks on a production data volume. After go-live, there's usually a two-week stabilization period where we monitor outputs and tune before handing off to your team. Healthcare builds add time for the BAA execution and data flow sign-off, which depends on how quickly the health system's privacy and compliance team can turn the review.