| What it does | Automated data verification that explains why numbers don't match across business systems
| AI workflows for public finance desks
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| Stage | MVP
| Startup
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| Founded | Not given
| 2025
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| Based in | Not given
| US
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| Pricing model | Free trial
| Not given
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| Pricing | Free tier available during beta with all features. Planned tiers: Pro (15 reconciliations, 15 schedules, 5 seats), Business (unlimited reconciliations and schedules, 25 seats), and Enterprise (everything unlimited with audit trail, single sign-on, security review, named contact, self-hosted or cloud
| Not given
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| Key features | - Connects to POS, ERP, e-commerce, WMS, CRM, SQL Server, Oracle, PostgreSQL, REST APIs, CSV and Excel
- Models data flow between systems and verifies reality against expected flow
- Identifies root causes like rejected records, mapping errors, or rule changes
- Runs on your own infrastructure with encrypted credentials
- Pre-built packs for Shopify, SAP, and Xstore systems
- Scheduled reconciliation and unattended automated checks
- Published apps and workspaces for sharing results across teams
- Audit trail with export for Enterprise tier
- Single sign-on authentication
- Learns and accumulates business context about system relationships over time
| - RFP and RFQ automation
- Issuer intelligence and records
- Private single-tenant deployment
- Integrates with existing systems
- Human approval at every decision point
- Forward-deployed support model
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| What makes it different | - Follows differences back to root causes instead of just reporting discrepancies
- Doesn't require replacing existing systems—sits across infrastructure you already have
- Never counts sources, drivers, or self-initiated runs—only counts what scales with users
- Runs locally on your infrastructure with no data leaving your network
- Learns business meaning and context behind data over time to explain system relationships
| - Designed exclusively for public finance desks, not horizontal platforms
- Customized to desk-specific workflows and approval standards
- Data never pooled or used to train models
- No system replacement or migration required
- Banker-engineer pairs stay through deployment
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | Not checked yet ▼ −18 (down) since last check | 2 ● no change since last check |
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| Trust Flow (Majestic) | 0 | 10 |
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| Citation Flow (Majestic) | 13 | 23 |
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| Referring domains (Majestic) | 45 | 25 |
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DataMosaic
Starch