AI-powered ETL platform purpose-built for UKG Ready. Stop debugging broken feeds at 3 AM. Our AI supervisor watches, learns, and fixes problems before they reach you.
📊 View Pitch Deck →Companies on UKG Ready
Integrations per company
AI solutions on market
The entire industry is running on hand-built scripts and 3 AM error emails. Nobody is solving this with modern technology.
Every integration is a snowflake — PowerShell, Python, SSIS. Each one hand-built, each one different, each one fragile.
Recordkeepers change specs without warning. UKG pushes updates. Date formats drift. A human gets an error email and manually debugs.
The same failure patterns repeat across clients. Fixes are never shared or codified. Every incident is solved from scratch.
New client integration? That's a custom development project. Weeks of field mapping, testing, and debugging before a single record flows.
When the person who built the scripts leaves, their institutional knowledge goes with them. Documentation? What documentation?
Failed 401k feeds = DOL penalties. Broken benefits files = uncovered employees. Payroll errors = people not getting paid.
A purpose-built ETL engine with an AI supervisor that watches every record, learns from every fix, and gets smarter with every client.
v1 Reports + v2 REST + Real-Time Webhooks
Pre-built connectors, delta sync, webhook listeners
Rules engine, field mapping, format conversion
The Differentiator — this is what nobody else has
SFTP/CSV, SQL Server, Azure SQL, Snowflake, API endpoints, recordkeeper formats
Every client, every fix, every failure makes the AI smarter. First mover advantage creates a moat that compounds over time.
With every fix
Companies on UKG Ready
Every one with external integrations is a potential customer.
Integrations Per Company
Benefits, 401k, payroll exports, GL feeds, recordkeeper feeds.
AI-Powered Competitors
Everyone is still doing regex and error codes. Nobody uses AI.
Based on $1,500-2,000 avg MRR per tenant + setup fees
Domain expertise + AI supervision + UKG partnership. That's the moat.
| Platform | UKG Depth | AI Supervisor | Auto-Remediation | Recordkeeper Feeds | Price |
|---|---|---|---|---|---|
| HCMNotify | ✓ Deep | ✓ Built-in | ✓ Learning | ✓ Native | $500-3K/mo |
| Merge.dev | ✗ Generic | ✗ None | ✗ None | ✗ None | Custom |
| Finch | ✗ Surface | ✗ None | ✗ None | ✗ None | Custom |
| Workato | ✗ Generic | ✗ None | ✗ None | Partial | $50K+/yr |
| Boomi | ✗ Generic | ✗ None | ✗ None | Partial | $50K+/yr |
| Custom Scripts | Varies | ✗ None | ✗ None | Manual | Engineer salary |
Per UKG Ready tenant. No per-seat nonsense.
24 years IT infrastructure & integrations. Deep UKG Ready API expertise. Built integrations for dozens of clients at Mosaic HCM / Vensure. Knows the pain firsthand.
15+ years in the UKG ecosystem. Deep relationships with clients, partners, and UKG corporate. The person who opens doors.
Custom AI system already in production. Built the proof-of-concept dashboard, webhook integrations, and automated reporting. Works 24/7.
Core components already proven in production. This isn't starting from zero.
Multi-tenant database, pipeline execution engine, UKG connectors (already proven), admin portal, basic dashboard.
Pattern playbook (seeded with 15+ years of fixes), AI intervention pipeline, human review queue, learning loop, anomaly detection.
Client portal, onboarding wizard, template pipelines, recordkeeper output formats. Launch with 2-3 pilot clients.
Apply for UKG Connect Partner Program, Marketplace listing, YouTube content channel, expand to 10 clients.
The Merbree Dashboard — a production multi-store restaurant management portal running live UKG integrations. Real data, real clients, real-time sync.
Token management, auto-refresh, both API versions working in production.
ModifiedTime-based incremental sync. Only processes what changed.
One API call for full datasets. Our secret weapon over v2 endpoint-hopping.
Real-time ACCOUNT_CREATED/UPDATED events from UKG. Instant response.
Full roster extraction, role-based access, pay rate security. Defense in depth.
Open punch detection, hourly labor distribution, multi-store aggregation — all live.
A detailed look at how the platform processes, monitors, and self-heals UKG Ready integrations.
Every record passing through the transform layer is captured. Schema validated, field types checked, null analysis performed.
Compared against the pattern playbook — a growing library of known failure signatures (format drift, value changes, missing data, collisions). Seeded with 15+ years of real-world fixes.
Statistical analysis across the dataset: record count deviations, value distribution shifts, sudden nulls, salary outliers, participant count drops. Each anomaly gets a severity score.
AI assigns a confidence score (0-100%) to its assessment. Above threshold (configurable per pipeline, default 85%) → auto-remediate. Below threshold → escalate with full context.
Every human review (approve/reject/correct) feeds back into the pattern playbook. Rejected fixes lower pattern confidence. Approved fixes strengthen it. New patterns are automatically created from novel corrections. The system gets smarter with every interaction.
14 tables across 5 domains. Multi-tenant by design. Every query scoped to tenant_id.
One API call returns a complete dataset — employees with pay rates, time entries with locations, payroll details. Returns human-readable CSV, not ID-heavy JSON.
✓ Bulk data extraction (employees, time, payroll)
Individual record operations, real-time event notifications. ACCOUNT_CREATED and ACCOUNT_UPDATED webhooks enable instant response to changes.
✓ Event-driven processing + individual updates
The hybrid approach is something nobody else does. Most integrators use v2 only — missing the efficiency of v1 saved reports entirely.
These aren't hypothetical. These are actual failure patterns from years of UKG integrations, codified for the AI to detect and fix automatically.
Recordkeeper changed expected format from XXX-XX-XXXX to XXXXXXXXX. AI detects the pattern shift, reformats all records, logs the change.
UKG updated "Bi-Weekly" to "Biweekly" in a release. AI maps the new value to the existing code, zero downtime.
401k eligibility file went from 847 to 612 participants. AI applies the fix but flags for human review — could be mass term or filter bug.
Recordkeeper added a new required field not in our mapping. AI blocks the load, surfaces the schema change, and suggests a mapping.
Source sending MM/DD/YYYY, destination expects YYYY-MM-DD. AI detects, converts, and continues. Logged but no human needed.
Employee pay rate changed from $85,000 to $850,000. AI flags as likely data entry error (extra zero), suggests correction, waits for confirmation.
We're selecting pilot partners now. Limited spots for early access.
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