Problems We Solve
TabulariumAI solves critical challenges that traditional systems cannot address:
Submission Rulebooks
Walk-In Recording: In-Person Precision, Operational Drag
Walk-in recording reduces submission errors through clerk interaction, but it requires physical visits, adds staff workload, and does not eliminate post-recording workflows—leaving delays, corrections, voided recordings, and refund processing in place.
- Submitters and clerks review documents, with corrections often requiring return visits.
- Onsite presence increases staffing demands, creates delays, and adds logistical burdens for all parties.
- Post-recording workflows can take 1 to 3 days and caught issues can lead to voids, refund cycles, or stalled filings.
TabulariumAI provides near-instant access to accurate indexes and fee calculations—allowing submitters to correct defects and allocate funds before submission. Its API supports AI-based refinement of notes and adjustments, filtering out invalid changes and aligning with clerk expectations. TabulariumAI delivers complete indexing and sensitive data detection upfront, removing post-recording workflows and eliminating delays, corrections, voided recordings, and refund processing.
eRecording: Faster Submission, Delayed Resolution
eRecording eliminates the need for physical delivery and speeds up submission, but it still relies on delayed clerk review and leaves post-recording workflows—such as redaction, corrections, and fee adjustments—intact.
- Documents may be rejected due to poor scans, formatting issues, or missing required elements such as signatures or notary stamps—leading to correction loops between the submitter and the registry.
- Fee miscalculations can halt recording until corrected and funds are reallocated.
- Post-recording corrections may result in voided recordings or refund processing.
- Processing often takes 1–3 days based on review capacity, putting escrow and closing timelines at risk.
TabulariumAI addresses these gaps by delivering complete, AI-extracted indexes, accurate fee calculations, and pre-submission refinement—all through API—minimizing rejections, accelerating approvals, and reducing downstream disruption.
Operational Complexity & Compliance Risks
Current Recording Systems: Complex, Rigid, and Heavy
Modern recording systems span cashiering, indexing, post-recording, and document management. Over time, they have become difficult to maintain, extend, and support due to jurisdictional variance and the broad scope of public document types.
- Extreme configurability—while necessary—has made these systems fragile and heavily reliant on local adjustments.
- Operational teams face constant support cycles for configuration changes, compliance updates, and issue resolution.
- Due to high cost and limited flexibility, these platforms are rarely profitable on their own and often serve as anchors for broader vendor ecosystems.
TabulariumAI complements these systems by automating title-class–specific tasks such as indexing, classification, redaction, and enrichment. As an API platform, it reduces front-end complexity and manual workload—offloading up to 70% of the document lifecycle while helping lower operating costs and support demands without requiring system replacement.
Incomplete Indexing and Public Risk
After certification, documents are assumed final—but indexes are often shallow, inaccurate, or missing critical context.
- Traditional indexing—often incomplete, misspelled, or lacking legal context—compromises downstream processes such as document retrieval, due diligence, title chain reconstruction, and other legal or transactional workflows.
- Sensitive content—such as account numbers, private agreements, or internal forms—is sometimes published in recorded documents due to manual review limitations and the narrow scope of redaction practices.
- Due to limited indexing, businesses often purchase entire document images to extract the specific data they need—introducing retention and compliance risks far beyond their actual requirements.
TabulariumAI resolves these issues by producing high-precision, legally contextual, and detail-rich indexes. This reduces full-document handling, supports targeted redaction, and limits unnecessary data exposure for downstream consumers.