Every industry has
the same AI problem.
The shape is different.
Five industries we know in our bones. What broke, what we built, and the metrics the board actually reads. Pick the one that looks like yours, or find yourself in all of them.
A claim isn't data.
It's a person waiting.
Prior authorization queues, manual intake summaries, care-plan drafting, the slow tissue of healthcare operations is where patient experience and margin are both lost. We shipped a CIM platform for a mid-market payer that took 14-day turnarounds to 36 hours, and made the compliance committee happier, not less so.
Agents pasted PDF claim data into five systems. Prior auth sat in a queue for 14 days on average. 9% of routine cases were escalated unnecessarily because the intake summary missed the context.
An evidence-grounded intake agent that reads the submission, pulls the policy, drafts a decision and a cited rationale. A human approves, never the other way around. Everything logs to audit from second zero.
Run team monitors drift every shift. Policy changes propagate in hours, not quarters. The board gets a monthly score on cycle time, appeal rate, and member-experience NPS, three numbers, one page.
"We are especially thankful for the leadership on last year's effort to launch our market-leading plan and the foundation-laying of our CIM platform."
Underwrite faster.
Explain every time.
Lenders and commercial insurers face a paradox, customers want instant decisions, regulators want traceable ones. We shipped a pre-screen agent and memo drafter for a commercial lender that cut cycle time by two thirds while adding, not removing, the audit trail.
Senior underwriters spent two days per file reading financials, cross-referencing covenants, and typing up memos. Committee meetings ran twice a week and 40% of cases were still waiting on one data pull.
A retrieval-grounded agent reads statements, flags covenant issues, drafts the credit memo, and cites every number back to the source doc. Underwriters review and sign, or override with one line of reasoning that audit gets to keep.
Every decision is reconstructable, model version, retrieval window, prompt, human override. Our Run team files quarterly model-risk evidence packets the first-line doesn't have to build from scratch.
Omnichannel is a
throughline, not a stack.
Every retailer with a 2018 digital strategy is now sitting on eight touchpoints that don't remember each other. Chat doesn't know the email. Email doesn't know the call. The customer does. Our Stevie Award-winning CIM platform turned that into a single, personalized thread, with recognizable economics.
A buyer starts in chat, gets escalated to email, calls two days later, and retells the story each time. NPS is fine. Retention is quietly bleeding. Marketing blames service. Service blames the CRM.
A chat-first personalization layer on top of Salesforce. Every interaction is summarized, scored, and threaded. Next-best-action is suggested to the rep, drafted in their tone, ready to send. Customer lifts are traceable to the specific touch.
Retention, expansion, cost-to-serve, all three reported monthly to the CEO from the same data layer. When a marketing promo changes, the assistant adapts tone and offer in hours, not sprints.
"Impressed by their transformative vision, especially for a chat-based personalized digital service."
Exceptions are the job.
We made them the system.
In logistics, nothing runs to plan. Weather, customs, carrier churn, a forklift that won't start. Planners spend all day on exceptions, and every exception is a phone call that didn't have to happen. We built an exception co-pilot for a global 3PL that turned the phone call into a 90-second acknowledgement, routed to the right person, first time.
Planners triaged exceptions across carrier portals, EDI feeds, Excel, and WhatsApp. High-value clients got phone calls. Everyone else waited. SLA penalties were a cost of doing business.
An exception agent that ingests telemetry, classifies severity, proposes a remedy with cost and ETA, and drafts the customer note, in the right language, with the right apology calibrated to the SLA. Planner approves and moves on.
Run team tunes severity thresholds by lane and season. Monthly read-out to the COO: exceptions prevented, SLA dollars saved, client-reported trust score, numbers that used to be stories.
"They told us what not to build. That was worth more than what they built."
Hiring is broken.
Both sides know it.
Recruiters are drowning in AI-written résumés. Candidates are ghosted by AI screeners. Meanwhile, every enterprise needs Agentic AI engineers, cloud architects, XR developers, roles where a traditional pipeline doesn't exist. myndQ is how we fixed it, end-to-end.
Recruiters screen 400 applications for one hire, most of them AI-embellished. Candidates send 80 applications to get three callbacks. Nobody trusts anything. The hire takes 84 days, if it happens at all.
For candidates: AI-conducted interviews, personalized learning pathways into Agentic AI, Cloud, XR, and Blockchain, curricula co-built with NVIDIA. For employers: verified skill profiles with evidence, SOC 2-ready, bias-audited.
myndQ for Business plugs into your ATS. myndQ TalentHub is open to any job seeker. We partner on cohort programs for employers committing to reskilling, the most durable way to solve the talent gap nobody's talking about.
your stack already runs on
Microsoft
Adobe
NVIDIAInception
Your industry
has a shape. Let's map it.
Three-week Diagnostic. Fixed fee. You walk out with a ranked shortlist and a board-ready brief, whether or not we continue.
platforms your stack
already runs on
Microsoft
Adobe
NVIDIAInception