Industries

AI consulting shaped for the way your industry actually works.

The useful AI questions are rarely generic. We connect AI strategy, RAG, agents, automation, and evaluation to the workflows, risks, records, and decisions an industry already runs on.

Services

strategy · RAG · agents · evaluation

Work style

industry context before tools

Base

Media, PA · Greater Philadelphia

Industry pages

Seven practical places to start.

Each page focuses on where AI can create leverage, where it can create risk, and what a serious engagement should produce before broader rollout.

01 Law firms Legal RAG, document review, knowledge workflows, and source-traceable AI. For firms that need useful AI without losing confidentiality, permission boundaries, citation discipline, or attorney review. Legal RAGPermissionsEvaluation 02 Healthcare Administrative AI that respects patient data and clinical boundaries. For healthcare organizations improving intake, communication, documentation, operations, and knowledge workflows with human oversight. IntakePHI-aware designReview 03 IT support & MSPs AI support workflows that make service desks faster and more consistent. Ticket triage, knowledge retrieval, escalation support, client documentation, and agent-assisted operations. TicketsRunbooksKB retrieval 04 Real estate AI-assisted diligence, development analysis, and repeatable deal review. For teams turning documents, site context, assumptions, and scenarios into clearer development decisions. DiligenceScenariosAnalysis 05 Professional services Reusable expertise, better proposals, stronger delivery systems. For advisory, consulting, engineering, and expert teams that need institutional knowledge to travel farther. Knowledge reuseProposalsDelivery 06 Financial & accounting Document-heavy AI with review, evidence, and client data discipline. For accounting, tax, advisory, and finance teams evaluating AI for research, intake, QA, reporting, and client service. Client docsResearchQA 07 Manufacturing & operations Operational AI for SOPs, quality review, maintenance, reporting, and visual workflows. For teams that need AI to support real operations: repeatable procedures, shift handoffs, inspections, maintenance knowledge, and measurable process improvement. SOPsInspectionMaintenanceOperations

What changes when AI work is shaped for your industry

The service categories stay familiar: strategy, RAG, agents, automation, evaluation, and leadership. What changes is the detail — the part that determines whether an AI system gets trusted, adopted, and operated after launch.

We start from the business context behind the model: the records people rely on, the approvals they cannot skip, the risks they have to control, and the evidence leadership needs before rollout.

01

Source material: contracts, charts, tickets, SOPs, deal files, or client records

02

Workflow: who reviews, approves, escalates, edits, or owns the output

03

Risk: confidentiality, compliance, accuracy, safety, client trust, or service quality

04

Evaluation: test cases drawn from real work, edge cases, and failure patterns

05

Rollout: a roadmap your leaders can defend and your team can operate

Next step

Have an industry-specific AI decision to make?

Start with the workflow, data, risk, or operating constraint that makes your situation different.