Real problems.Intelligentoutcomes.
From the clinic to the classroom. From the first lead to the next sale. Explore 32 ways we turn complex workflows into AI that works.
Give clinicians their day back
Documentation, prior authorization, patient access and revenue cycle — rebuilt on multi-agent pipelines that write straight into Epic, Cerner and 100+ other systems.
The 70 Percent Problem: Fixing Clinical Documentation With Multi Agent AI
A three-agent pipeline that transcribes the visit, drafts the specialty note with ICD-10 and CPT codes, and reviews it against the chart before the physician ever sees it.
Ending the 13 Hour Week: Automating Prior Authorization
Payer policy retrieval, chart-sourced clinical justification, and cross-channel submission — staff are interrupted only for denials and peer review.
The 200 Dollar Empty Chair: Reducing No Shows With Voice AI
Conversational outbound confirmations, a 24/7 inbound line, voice-collected pre-visit intake, and automatic waitlist fill the moment a slot opens.
Turning Scattered Clinical Guidelines Into an Assistant Every Provider Can Ask
Protocols, formularies and SOPs embedded into a permission-scoped vector index, answered with an inline citation back to the source document and page.
From PDF Pile to Patient Timeline in Seconds
OCR and extraction across scanned faxes, handwritten forms and lab exports, assembled into one chronological timeline with clinically significant events flagged first.
Read the use caseCatching the Signal Before It Becomes an Emergency
Continuous ingestion from wearables, home devices and the EHR, with anomaly detection tuned to each patient's own baseline rather than a flat population threshold.
Read the use caseSupport Between Sessions: An AI Companion That Extends Care, Not Replaces It
Clinician-reviewed CBT and DBT conversation flows, with a safety classification pass running on every message before a response is ever generated.
Read the use caseThe Silent Revenue Leak: Preventing Claims Denials Before They Happen
Pre-submission scrubbing against payer rules and the actual encounter note, plus RAG-grounded appeal drafting for the claims that still come back denied.
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Answer first, win the listing
Voice qualification inside five minutes, a pipeline that scores itself, and portal syndication from a single listing entry — live in production in Australia today.
917 Minutes: The Real Cost of a Slow Response in Real Estate
An outbound voice agent that calls a new inquiry within minutes, qualifies it in natural conversation, scores it 0–100, and routes the hot ones with full context attached.
Turning Midnight Browsers Into Booked Inspections
A listing-site assistant that gathers requirements conversationally, matches them against live inventory through a direct API query, and creates a fully contexted lead on its own.
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What Happens After the Open Home Is Where Most Agencies Drop the Ball
QR code check-in that writes straight into the CRM, then interest-level segmentation that decides whether an attendee gets a call within hours or an SMS sequence.
Read the use caseReading Every Rental Application in Minutes Instead of Days
Pay stubs, ID scans and reference letters parsed into one applicant schema, with affordability ratios calculated automatically and cross-document mismatches flagged before a decision.
Read the use caseEvery Maintenance Request Deserves a Fast Answer, Not a Voicemail
Calls, texts, chats and emails funnelled into one queue, then classified by urgency and trade so a burst pipe never waits behind a light bulb.
Read the use caseReplacing the Spreadsheet Pipeline With One That Scores Itself
Lead scores that update on every new signal, probability-weighted commission forecasting that rolls up in real time, and stale leads that raise their own follow-up task.
Read the use caseOne Click to Every Portal: Ending Duplicate Listing Entry
A single listing entry generating properly formatted feeds for every connected portal, with inbound inquiries normalized back into one pipeline and tagged by source.
Read the use caseBuilding a Defensible CMA in Minutes, Not an Afternoon
Comparable sales retrieved through existing portal integrations and assembled into a branded, client-ready draft where every figure links back to its source record.
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Sell like your best associate
A catalog-grounded assistant that compares products and handles objections, cart recovery that does not lean on discounts, and compliance verification for regulated categories.
Replacing the Static FAQ Widget With a Sales Assistant That Actually Sells
A catalog-grounded assistant that compares products and handles objections, refreshed against the live inventory feed and carried across web, WhatsApp and WordPress.
The 70 Percent Problem: Recovering Revenue That Is Already Walking Out the Door
Objection-aware recovery copy generated from the actual cart contents, timed by intent score across email, SMS and WhatsApp — without training shoppers to wait for a coupon.
Support That Never Clocks Out: Automating the Repetitive 80 Percent
Order status read live from the order management API, returns actioned within explicit policy limits, and anything outside those bounds handed to a human with full context.
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Selling Regulated Products Online Without Betting the Business on a Chatbot’s Mistake
A generate-and-verify dual agent architecture: an independent verification agent checks every draft against a configurable rule set, and a failed check is held for human review, never auto-corrected.
Read the use caseThe Sale Is Not the Finish Line: Automating What Happens After Checkout
Product-specific lifecycle scheduling at the moment of purchase — replenishment timed to real consumption cycles, cross-sells grounded in the catalog index, reviews gated behind first use.
Read the use caseAnswering Every Call: Voice AI for the Customers Who Still Want to Talk to Someone
Natural call handling with real-time availability checks, order taking or booking completed on the call, and a structured summary written back to the CRM automatically.
Read the use caseWhy Your Site Search Is Losing Sales, and How AI Rebuilds It Around Intent
The same vector index behind the sales assistant, pointed at the search bar — plus an enrichment agent that fixes thin supplier-feed listings before they ever reach the index.
Read the use caseThe Cost of Saying Yes to Everyone: Catching Fraud Without Punishing Good Customers
A continuous risk score rather than a binary flag — low-risk customers clear instantly, the ambiguous middle routes to human review, and confirmed outcomes feed back into the model.
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Ten hours a week, returned
Rubric-faithful automated grading, four-skill language assessment, and AI coaches trained on an institution's own curriculum rather than generic internet content.
Giving Teachers Back Ten Hours a Week Without Lowering the Bar on Feedback
Each rubric criterion becomes its own evaluation pass, and every generated score lands in a teacher review queue — a first-pass draft grader, never a black box final authority.
Testing Every Language Skill at Once, and Grading All of Them Instantly
Speaking scored from streamed audio against a spoken-assessment rubric, listening prompts generated by TTS, and all four modules writing into one scoring engine.
One Tutor Per Student, Without Hiring One Tutor Per Student
Coaches grounded in the institution's own curriculum and explanation style, across chat, audio and video, adapting pacing to each student's real performance over time.
Answering Every Prospective Student’s Question Before They Apply Elsewhere
Program pages, policy documents and deadline calendars indexed for retrieval, live application status lookups, and complex cases routed to a human counselor with context attached.
88 Percent of Students Use AI on Assignments — Assessment Has to Catch Up
Identity verification and behavioral monitoring during the session, with AI-assistance flags on written work routed to a human reviewer alongside the evidence, never auto-failed.
Spotting the Student About to Fall Behind, Weeks Before Anyone Else Does
LMS and gradebook signals tracked continuously into a weekly risk score, presented to advisors with the matching intervention and the trend that triggered it.
Read the use caseThe Course Q&A Channel That Never Sleeps and Never Repeats Itself
Syllabus and assignment material indexed per course section inside the existing LMS, with a classifier separating logistics questions from conceptual ones that belong with the instructor.
Read the use caseMaking Every Lesson Available in the Language and Format a Student Actually Needs
The speech pipelines built for language assessment, pointed at course materials instead of test content — with a translation layer on top of the same source content.
Read the use caseDo any of these look like your problem?
Most of these started as a single workflow someone wanted to stop doing by hand. Tell us which one is costing you the most, and we will show you the system we would build for it.