AI Integration

AI connected to your real operations — not a chatbot demo.

There's a difference between using ChatGPT and having AI integrated into your business. We build the latter — document processing, intelligent routing, decision support — wired into the systems your team already uses.

Assess AI Readiness — Free Talk to an Engineer

Example: Document Intake Automation

AI processes what it's confident about — anything uncertain routes to a human. No bad data enters your system.

What We Build

AI that changes operational outcomes — not demo tools

These are the AI integrations that produce measurable time and cost savings when connected to real workflows.

Document Processing

Contracts, invoices, intake forms, emails — AI reads unstructured documents, extracts structured data, and writes it to your systems automatically.

Invoice extraction → accounting
Contract clause identification
Email triage & data extraction

Intelligent Routing

Requests, tickets, and leads get classified, prioritized, and routed to the right queue before a human reads them. Response time compresses dramatically.

Support request classification
Lead quality scoring on intake
Priority escalation routing

Internal Knowledge Q&A

Connect an AI model to your policy library, documentation, or knowledge base. Staff query it naturally instead of hunting through folders or asking a manager.

Policy & procedure Q&A interface
Staff onboarding knowledge system
Connected to your actual documents

AI-Assisted Reporting

Reports, summaries, status updates — AI drafts these from structured data inputs and delivers them on schedule, without manual initiation.

Automated weekly ops summaries
Meeting transcript → action items
Data → narrative report generation

Data Classification

Unstructured emails, notes, and tickets carry information that's hard to query. AI adds categories, sentiment, entities, and metadata automatically.

Auto-tagging incoming communications
Sentiment analysis on feedback
Entity extraction (names, dates, amounts)

Decision Support

Some decisions need a rule applied to data. Others need human judgment — but benefit from an AI brief first. We design exactly where that boundary sits.

Rules-based auto-approval flows
AI briefs for human review
Risk scoring on applications

AI Readiness

Is your organization ready for AI integration?

AI delivers real value when your data is structured, your processes are defined, and you have specific problems to solve. We assess readiness before recommending investment.

✓ Ready for AI Integration

✓ Recurring document processing done manually

✓ Defined intake or support workflow needing triage

✓ Internal documentation staff queries repeatedly

✓ Recurring reports from structured data

✓ Data flowing through multiple systems

✓ You can define what "correct output" looks like

✗ Not Ready Yet — Fix First

✗ Data is siloed, unstructured, or not in digital form

✗ Processes aren't defined enough to describe

✗ Solving a problem you haven't diagnosed yet

✗ No mechanism to measure whether AI is correct

✗ Systems don't yet have API access

✗ Expecting AI to replace judgment on unvalidated use cases

If you're in the "not ready yet" column

That's what the operations audit is for. We fix the data and systems foundation before recommending any AI investment. See also: workflow automation to connect your systems first.

Integration Architecture

Model-agnostic. No AI vendor lock-in.

We work with OpenAI (GPT-4o), Anthropic (Claude), Google (Gemini), and open-source models (Llama 3, Mistral, Phi) depending on the use case, data sensitivity, and budget.

We design the integration layer so the AI model can be swapped without rebuilding the workflow. Your system isn't tied to one vendor's roadmap or pricing changes.

Data Privacy First

For sensitive data (student records, donor info, healthcare-adjacent), we architect integrations that keep private data out of third-party model contexts — using local models, data anonymization, or retrieval architectures that keep sensitive data in your environment.

// AI Intake — Confidence-Gated

const raw = await inbox.fetchNew();

const structured = await ai.extract({
  input: raw.content,
  schema: invoiceSchema,
  model: "gpt-4o" // swappable
});

if (structured.confidence > 0.92) {
  await db.insert("invoices", structured.data);
  await accounting.createBill(structured.data);
} else {
  await queue.push("review", { raw, structured });
}