E-commerce / DTC
Run a store. Not operations.
Most DTC brands are paying people to do things software should handle. Order routing, inventory alerts, supplier messages, product descriptions, customer replies - all of this can be automated. Our client Simbago runs $8k/month with one warehouse worker.
Case study: Simbago - 1 employee, $8k/mo ->Order processing
Auto-route orders to warehouse, send confirmations, update tracking - zero manual steps.
Customer support
80% of support questions answered by AI. Shipping status, returns, product questions. Escalates edge cases.
Inventory reordering
Stock hits threshold, supplier message goes out automatically. No stockouts, no manual checks.
Product content
Upload new SKUs, get descriptions, alt text, and social posts generated in your brand voice.
Review management
New reviews flagged, drafted responses generated, sent after approval or auto-published.
Returns processing
Return request triggers label generation, refund initiation, and replacement order if applicable.
B2B / Sales
More pipeline. Same team.
B2B sales breaks down at volume. Manual list building, inconsistent follow-up, CRM that nobody keeps clean. We automate the ops layer so your reps focus on closing. One client went from 5x outreach volume with no new hires.
Case study: B2B Pallets - 5x outreach, no new hires ->Lead list building
Clay or Apollo pulls, enriches, and scores leads by ICP criteria automatically. Updated daily.
Cold outreach sequences
Personalized emails triggered by signal data - job changes, funding rounds, new hires. Send at scale.
AI qualification calls
Vapi.ai handles the first qualification call. Asks the right questions, scores the lead, routes warm ones to a human.
CRM hygiene
Contacts auto-updated from email activity. Deal stages move when emails are replied to. No manual updates.
Follow-up sequences
No reply after X days triggers the next message automatically. Nothing falls through the cracks.
Meeting prep briefs
Before every call: AI brief with company news, contact info, past interactions, suggested talking points.
Agencies
Deliver more. Bill the same.
Agencies are stuck in a loop: more clients means more headcount. AI breaks that. Client reporting, content production, onboarding, proposal writing - we automate the parts that don't need a human so your team does the parts that do.
Case study: Persij - team 2x output, zero new hires ->Client reporting
Pull all client metrics, calculate KPIs, write executive summaries, email to clients. Every Monday, automatically.
Content pipeline
Brief goes in, first draft comes out. Claude writes in the brand voice. Team edits and approves. 3x output.
Client onboarding
Contract signed triggers: welcome email, questionnaire, doc request, kickoff scheduling. Consistent every time.
Proposal generation
Input client name and brief, get a structured proposal draft in 2 minutes. Customize and send.
Social scheduling
Approved content goes into a queue, scheduled across platforms at optimal times automatically.
White-label delivery
We build under your brand. Full NDA. Your clients never know we exist.
Finance / Trading
Faster analysis. No analyst dependency.
Trading desks and finance teams are bottlenecked by manual analysis. Chart reading, document review, reconciliation, reporting - these are pattern recognition tasks. We built a custom neural network for one trading desk that cut their morning analysis from 2 hours to 10 minutes.
Case study: Trading desk - 2hr morning analysis → 10min ->Market signal generation
Custom model scans 30+ instruments, generates entry/exit signals with confidence scores in real time.
Document processing
Invoices, contracts, statements - parsed, categorized, matched against records automatically.
Invoice reconciliation
Thousands of documents matched monthly against purchase orders. Discrepancies flagged, matches approved.
Trade briefs
Claude converts raw signals and market data into readable trade briefs with full reasoning attached.
Compliance document prep
Structured data extracted from regulatory docs, formatted into required templates.
Reporting automation
Daily/weekly reports generated from live data, formatted, distributed to stakeholders.
Logistics / Operations
Eliminate the paperwork layer.
Document intake
PDFs, scans, emails with attachments - ingested, parsed, and routed automatically by document type.
Invoice matching
Incoming invoices matched against POs in the system. Auto-approved if matched, flagged if not.
Shipment tracking updates
Status pulled from carrier APIs, formatted, and sent to recipients at each milestone automatically.
Supplier communication
Reorder triggers, delivery confirmations, discrepancy notifications - sent without human drafting.
Exception handling
Only mismatches above threshold route to a human approver. Everything clean gets processed automatically.
Monthly close
Reports compiled from reconciled data, formatted, and distributed. Close time drops from days to hours.
iGaming / Casino
Per-player retention, not cohort blasts.
Online casino retention is mostly done by hand. Analysts build cohorts, push the same bonus to everyone in the segment, and the signal that a single player is about to go silent gets averaged away. We build the scoring layer: a gradient boosting model on raw transactions returns a churn and reactivation probability per player, with the features that drove the score, into the operator's existing retention CRM. We score; the operator owns the bonus, the script, and the telco cost.
Case study: European online casino - per-player scoring pilot ->Per-player churn scoring
Gradient boosting model returns a churn probability for the next 7-30 days per active player, with the features that drove the flag. Auditable, not hallucinated.
Per-player reactivation scoring
For silent players, a second model returns the probability of reactivation if contacted. Outreach goes to players the model believes will respond.
Prioritized worklist into the existing CRM
Both scores flow into the operator's retention CRM as a daily worklist. We do not replace the team or the workflow. We upgrade the prioritization.
Account-type and consent filtering
Test, service, and bot accounts are filtered out of training. Self-exclusion and responsible gaming flags are checked before any retention trigger fires.
Adapter for self-written platforms
We map the player schema to a standard feature card once, then read from the source tables. No migration off the existing platform.
Optional outbound trigger
For operators without an internal team, the scoring service fires triggers into a connected dialer or messaging stack under the operator's telco account.
Medical / Health
Patient ops without ops staff.
Patient intake
Structured intake via chat or form. AI pre-screens, asks follow-up questions, collects all required info.
Qualification
AI pre-qualifies patients against clinical criteria before any human reviews the case.
Provider matching
Patient profile matched against provider criteria, capacity, and availability automatically.
Appointment coordination
Scheduling across time zones, reminders, document requests - all automated sequences.
Document collection
Patients prompted for specific documents. Follow-up if missing. Organized before review.
Follow-up sequences
Post-consultation check-ins, feedback requests, and conversion sequences triggered automatically.
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