Starterstack

Starter Stack serves lenders funding approximately $50M–$500M annually across:

• Revenue-Based Financing (RBF)
• Commercial Real Estate (CRE)
• Private Credit
• Asset-Based Lending (ABL)

Its team includes Mark Dusseau, Co-Founder, with more than 10 years of experience in fintech and alternative lending operations, and Jane Doe, Head of Lending Solutions, with more than 10 years in fintech and loan origination systems.

Starter Stack is an official Anthropic Implementation Partner and a member of the American Association of Private Lenders (AAPL).

Advisory — $5,000 per month

Starter Stack maps workflows, designs the target system, and provides a rollout plan. The customer's team performs the build.

Deployment — $7,000 per month

Starter Stack designs, builds, and connects selected workflows, then runs them on its automation stack. The customer sets the rules.

Managed — $9,000 per month

Starter Stack identifies bottlenecks and designs, builds, runs, and tunes multiple workflows as a managed operations layer.

For suitable workflows, outcome-based pricing may also be available based on a share of measured cost savings or net new revenue.

Contact

• Email: support@starterstack.ai
• Address: 1055 Howell Mill Rd 8th Floor, Atlanta, GA 30318
• Hours: Monday–Friday, 8:00 AM–6:00 PM ET

Starter Stack is headquartered in Atlanta and offers a 30-minute demo covering current workflows and the application of Document Intelligence and Risk Monitoring to a lender's operation.

Supported documents include:

• Bank statements
• Tax returns
• Rent rolls
• Invoices
• Lease agreements
• UCC filings
• Loan agreements
• Borrowing base certificates
• Custom forms

The system can flag missing stipulations, search document libraries, detect stacking risk, and export structured data to an LOS, CRM, spreadsheet, REST API, webhook, or CSV download. No template configuration is required for custom forms.

Automated process

1. Ingest PDFs, images, scanned files, or multi-page packages through an API or drag-and-drop.
2. Classify document types automatically.
3. Extract and normalize fields such as revenue, expenses, NSF counts, average daily balances, collateral values, and maturity dates.
4. Cross-validate information and surface discrepancies.
5. Deliver structured data and decision-ready summaries to existing systems.

Starter Stack states that the service provides 97%+ field-level extraction accuracy on standard lending documents, processes bank statements in under 30 seconds, and can process documents within days of onboarding.

The engagement model has three stages:

1. Strategy: Diagnose the operation and design the required agentic workflows.
2. Implementation: Build AI agents and normalize messy data inputs.
3. Infrastructure: Run the system on Starter Stack infrastructure while securely processing the lender's data.

Common starting points

• Underwriting intake and document review: Structure borrower files, flag missing stipulations, and extract data from statements and tax returns.
• Portfolio monitoring: Watch for risk drift, stale payments, and covenant movement.
• Servicing handoff: Preserve deal context after closing and flag unusual cases to named owners.
• Finance operations: Reconcile servicing data, bank activity, and accounting records.

Implementation timeline

During the first phase, the team speaks with staff about originations, underwriting, servicing, and finance. It then maps responsibilities and friction points, selects the first workflows to automate, and defines where humans remain in control. The first workflow is intended to go live within 30 days, with ongoing tuning afterward.

The system monitors:

• Debt-to-EBITDA
• Fixed Charge Coverage Ratio
• Current Ratio
• Payment patterns
• Covenant thresholds and warning bands
• CRE occupancy rates
• CRE NOI trends
• CRE DSCR compliance

When a ratio approaches or crosses a warning or covenant threshold, the system sends an alert to the assigned portfolio or workout manager with a structured covenant summary. Ratios are stored in a time-series database so teams can review trend direction as well as point-in-time compliance.

Portfolio Monitoring is designed to help lenders identify risk drift and covenant issues earlier, giving teams time to consider actions such as restructuring terms, increasing reserves, or exiting positions before defaults occur.