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Use cases

The kind of systems we can build

Illustrative examples of systems we can build, the kind of problem they solve, how we'd approach them, and the kind of result they're designed to produce.

These are illustrative examples of what we can build, not client engagements, and they carry no measured results.

Summarize with AI:ChatGPTClaudePerplexity
Fintech & Lending
Read & verifyFinancial documents, automatically

Document intelligence for loan processing

An intelligent document pipeline that reads, extracts, and verifies financial documents, so the same analysts can handle far more, with every decision auditable.

See the example
Manufacturing & Industrial
Surface wasteHidden operational inefficiency

Surfacing hidden waste with operational intelligence

A system that connects fragmented operational data, predicts outcomes, and flags the waste that spreadsheets miss, turning scattered data into decisions.

See the example
E-Commerce & D2C
Resolve, not deflectRoutine support, end to end

Customer intelligence that resolves, not deflects

A customer-intelligence system that genuinely resolves routine interactions, predicts churn, and personalizes, connected to the helpdesk and store, with clean handoff to humans.

See the example
Legal & Law Firms
Review the 10%First-pass relevance and privilege triage

Discovery and document-review triage for litigation

A document-review triage system designed to read a discovery set, flag likely-relevant and potentially privileged documents, and route the ones worth an associate's eyes, so the team reviews the fraction that matters instead of billing hours across everything.

See the example
Logistics & Freight
Minutes, not hoursEmailed RFQs quoted while the load is open

Quote-from-email automation for freight brokers

A quote-from-email system designed to read the RFQs that land in a broker's inbox, pull the lane, equipment, and dates, rate them against your own history and benchmarks, and draft a priced reply in minutes, so a faster broker doesn't cover the load first.

See the example
Construction & Contractors
Photos you already takeProgress and hazard flags for a human

Site-photo progress and safety monitoring

A computer-vision system designed to run over the site photos your crews already take, surfacing progress against the schedule and flagging potential safety hazards like missing PPE or unguarded edges for a superintendent to review, never to sign off on a site's safety.

See the example
Dental & Specialty Clinics
Verified before seatedEligibility documented ahead of the visit

Insurance verification and prior-auth before the visit

A front-office system designed to check eligibility, benefits, and prior-authorization before a patient is seated, reading payer portals and your PMS so coverage is confirmed and documented ahead of the visit. Purely administrative: it never touches anything clinical or diagnostic.

See the example
Insurance Agencies & Claims
Read into your AMSACORDs and loss runs extracted for a CSR

ACORD submission intake into your AMS

A submission-intake system designed to read ACORD forms, applications, and loss runs as they arrive, extract the fields, and land them in the right account and policy record in your AMS, with quoting prepped before a CSR opens the file. A licensed human always makes the coverage call.

See the example
E-Commerce & D2C Brands
Stock to what's comingSKU-level demand from your sales history

Demand forecasting for a D2C brand

A demand-forecasting model designed to predict sales by SKU from a D2C brand's own order history, promotions, and seasonality, so buying and inventory decisions are made against a forward view instead of gut feel and last year's spreadsheet, with honest error bars on every number.

See the example
Recruiting & Staffing
Redeploy, don't re-sourceFitting past candidates ranked for a recruiter

Candidate rediscovery and matching over your ATS

A matching system designed to score your own ATS history against a new requisition, resurfacing past candidates who fit before a recruiter re-posts the job board. It ranks and surfaces options for a human to decide, and never auto-rejects or makes a hiring call on its own.

See the example
Accounting & Bookkeeping
Close, earlierCategorization with anomaly review queues

Month-end close acceleration

A month-end system designed to categorize transactions and reconcile ledgers across every client's books, surfacing only the true anomalies for review, so the mechanical work that delays a close runs on its own and a CPA spends the time on judgment and sign-off, earlier in the month.

See the example
Real Estate & Brokerages
Deadlines chased for youContract-to-close, nothing slips

Contract-to-close transaction coordination

An agentic assistant designed to run the contract-to-close process, tracking every deadline, missing disclosure, and outstanding signature across live deals, and chasing the right party before a date slips, while a transaction coordinator keeps the judgment calls and the system escalates when it isn't sure.

See the example

Your problem could be the next one.

Tell us what you're trying to fix or build. We'll map the system and scope it with you.

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AI automation, agents, computer vision, and forecasting, built to production for growing businesses and handed over in full: code, models, and documentation.

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