PING—fintech+lawtechplatformforSMB
A platform for SMB: financial health monitoring and debt collection. Before — spreadsheets and letters. After — real-time alerts and automated legal procedures.
In brief
Fintech + lawtech: agents watch receivables, predict risk and run the legal recovery procedures. The case explains the original process, implementation stages, available public outcomes, solution limits and the questions another company should verify with its own data before a pilot.
Key takeaways
- +41% — debt recovery uplift
- Success is evaluated through an accepted process and verified evidence, not a model promise.
- 8 wk — to first version
PING — a platform for SMB. Receivables are the main hole in SMB cash flow. We built a platform that joins financial monitoring with a legal pipeline: it tracks overdue invoices, predicts risk, runs the pre-trial procedures itself and hands the case to court if needed.
Architecture and process
The receivables platform separates obligation ingestion, party identity, calendar, communication, documents and legal escalation. Every status has a basis and date. Automation proposes the next step, while legal action requires authority and a verified document.
Public evidence boundary
The public page contains only the first-party facts approved for disclosure. Private architecture, personal data, contracts and internal logs are intentionally excluded.
What to validate before reuse
Another market must validate jurisdiction, time limits, communication consent, debtor identity, dispute process and personal-data handling. Financial results depend on portfolio and execution; public performance is not a recovery promise.
How we built it
Financial pulse
The platform plugs into 1C, the bank and CRM in an hour. An agent computes DSO, cash-gap and per-client default probability.
Debtor scoring
The model ranks debtors by risk. The owner sees where money is stuck and where it's about to be lost.
Legal pipeline
A lawyer-agent drafts the claim, sends it, tracks the response, prepares the lawsuit by the court's template.
Single panel
One screen — finance and legal together. The owner sees where the money is and when it returns.
Verification and operating handoff
The team compares accepted outcomes with evidence and documents limitations, access, monitoring and fallback. The process owner accepts the system only after a real-scenario check. Version changes trigger reassessment; an unverified effect never becomes a public promise.
What came out
A similar process? Let us assess the impact first
We will review the task, data and metric. If a pilot is unnecessary or AI is the wrong fit, we will say so before any work starts.
Limitations and risks
- The outcomes belong to this specific project and do not guarantee the same effect in another company.
- The public version does not disclose confidential data, personal information or private infrastructure details.
Questions and answers
What problem did the PING project address?
PING — a platform for SMB. Receivables are the main hole in SMB cash flow. We built a platform that joins financial monitoring with a legal pipeline: it tracks overdue invoices, predicts risk, runs the pre-trial procedures itself and hands the case to court if needed. Public metrics from this project are not a guarantee for another organization.
How did Aiconic structure the work?
Financial pulse: The platform plugs into 1C, the bank and CRM in an hour. An agent computes DSO, cash-gap and per-client default probability. Debtor scoring: The model ranks debtors by risk. The owner sees where money is stuck and where it's about to be lost. Legal pipeline: A lawyer-agent drafts the claim, sends it, tracks the response, prepares the lawsuit by the court's template. Single panel: One screen — finance and legal together. The owner sees where the money is and when it returns. Public metrics from this project are not a guarantee for another organization.
Can another company expect the same result?
The outcomes belong to this specific project and do not guarantee the same effect in another company. The public version does not disclose confidential data, personal information or private infrastructure details. Public metrics from this project are not a guarantee for another organization.
Sources and evidence
- NIST Privacy Framework
Privacy and data-lifecycle management.
- Secure Software Development Framework
Secure software lifecycle practices.
Aiconic Editorial Team · This material was prepared with AI tools in an Aiconic editorial session. Facts and wording are limited to published project data.
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