AI & Automation — Business Scenarios
Timesheets & Job Costing0:00 / 3:39Rotate your phone or tap ⛶ for a readable full-screen view.
Knowledge Assistant0:00 / 4:17Rotate your phone or tap ⛶ for a readable full-screen view.
Proposal Assistant0:00 / 5:30Rotate your phone or tap ⛶ for a readable full-screen view.
Product Content Operations0:00 / 4:49Rotate your phone or tap ⛶ for a readable full-screen view.
Invoice & AP Processing0:00 / 4:51Rotate your phone or tap ⛶ for a readable full-screen view.
Field Inspection & Digital Forms0:00 / 4:22Rotate your phone or tap ⛶ for a readable full-screen view.
Customer Portal0:00 / 4:40Rotate your phone or tap ⛶ for a readable full-screen view.
DoD Bid Intelligence0:00 / 5:51Rotate your phone or tap ⛶ for a readable full-screen view.
AI RFQ Assistant0:00 / 4:29Rotate your phone or tap ⛶ for a readable full-screen view.
AI Workflow Assistant0:00 / 4:27Rotate your phone or tap ⛶ for a readable full-screen view.
AI Reporting Assistant0:00 / 4:54Rotate your phone or tap ⛶ for a readable full-screen view.
Variedy

Business Scenarios

Seven patterns from real business situations, plus three production-style walkthroughs. Each starts with a common business challenge and shows how AI and automation can reduce manual work, improve decisions, and deliver measurable value.

PATTERN 01AUTOMATE

Timesheets & Job Costing

Anna's Friday disappears into chasing timesheets. Automate the chase and the costing — keep her judgment.

PATTERN 02ASSIST

Knowledge Assistant

Every question goes to Frank. AI understands the question and reasons over the plant's own manuals, SOPs and work orders — Frank reviews, he doesn't write.

PATTERN 03ASSIST

Proposal Assistant

Marcus loses 2–3 days per proposal. AI understands the bid and synthesizes a first draft from approved knowledge; experts keep the technical approach.

PATTERN 04AUTOMATE

Product Content Operations

Denise re-types every product update into five places. One update in, five approved outputs out.

PATTERN 05AUTOMATE

Invoice & AP Processing

Priya's team keys 340 supplier invoices a month and chases approvals. Extract, match, route — people decide the mismatches.

PATTERN 06AUTOMATE

Field Inspection & Digital Forms

Marco's site inspections live on paper — photos on phones, forms in trucks, disputes with no evidence. One phone form replaces all of it.

PATTERN 07AUTOMATE

Customer Portal

Lena's inbox is order-status questions. A portal where customers see status, download documents and reorder — with AI answering from their own orders.

PATTERN 08ASSIST · INTELLIGENCE

DoD Bid Intelligence

A real Army solicitation lands. AI understands the opportunity, finds what changed in the amendments, matches the requirements to the company's own evidence, writes the first-pass response and flags the exceptions — people review, decide and approve.

Production-style walkthroughs

Three deeper walkthroughs of AI-in-the-loop workflows — the same philosophy with more moving parts. Each opens full-screen with its own guided controls.

WALKTHROUGH 01

AI RFQ Assistant

From customer email to an approved quote — including a learning loop where every new pricing rule needs human sign-off.

WALKTHROUGH 02

AI Workflow Assistant

A customer order-status request understood, researched, answered and escalated — with a person approving the reply.

WALKTHROUGH 03

AI Reporting Assistant

Three spreadsheets become a distributed weekly report — deterministic pipeline, with AI only where it earns its place.

AI RFQ Assistant

Hartwell Components · a customer email becomes an approved quote. The salesperson approves every recommendation, and a pricing correction only becomes a rule after explicit sign-off.

Your numbers — quotes won back

—illustrative added gross profit/yrvs indicative build slice $8K–$12K · full $18K–$33K
Illustrative — assumes same-day quotes lift your win rate by the percentage you enter. Your assumptions, not a guarantee; final scope and price are set after joint discovery.
ProblemQuotes take days; pricing lives in a few heads
ExceptionUnusual volume → human approval; a correction becomes a proposed rule needing sign-off — pricing never changes silently
AI · AutomationAI understands the request, gathers the company context and reasons to a recommendation · rules price within approved limits, route, and record to CRM
Measure · NextQuote turnaround, quotes/week, win rate → order entry, pricing intelligence, CRM automation
Controls are inside the walkthrough below.

AI Workflow Assistant

Internal operations — the team's side of a customer request: understood, researched across order, shipping and inventory systems, drafted, and approved by a person before any reply goes out.

Your numbers — status calls priced

—team time recovered/yrvs indicative build $7K–$11K · $75–$350/mo
Illustrative based on stated assumptions — team capacity recovered, not guaranteed hard-dollar savings.
ProblemEvery status request is a manual lookup across systems and a hand-written reply
ExceptionInsufficient information or an urgent line → escalated to a person before any reply
AI · AutomationAI understands the request, connects it to the order and identifies what matters · rules gather from systems, route, and record
Measure · NextResponse time, contacts/week, escalations → internal service requests, approvals, exception queues
Controls are inside the walkthrough below.

AI Reporting Assistant

Deterministic first — rules consolidate and validate three spreadsheets; AI then analyzes the results for meaningful anomalies, explains what they mean and turns them into a management narrative with recommended actions. Inconsistent source data stops the report for review.

Your numbers — reporting days back

—illustrative reporting capacity recovered/yrvs indicative build $5K–$8K · $25–$85/mo
Illustrative — people × hours/month per person × loaded cost × 12. Capacity that can be redirected to analysis and action; your assumptions, not a guarantee. Final scope and price are set after joint discovery.
Problem~4 hours every Monday morning, before any decision gets made
ExceptionMissing or inconsistent source data halts the report for a person — nothing is smoothed over
AI · AutomationRules consolidate, validate and calculate · AI interprets the results, identifies what matters, explains why and recommends what to review
Measure · NextHours per cycle, days to distribution, data issues caught → dashboards, forecasting, data quality
Controls are inside the walkthrough below.