Syftics™ understands M-Pesa transaction patterns and local data structures — because it was built around them from day one.
An AI data analyst purpose-built for African financial data. Syftics™ understands M-Pesa transaction patterns and local data structures, and surfaces the insights that matter in them.
Mobile-money statements, till and paybill structures, and agent-network transaction patterns have their own structure and rhythm. Syftics™ was built around them from the start.
Parses paybill, till, and agent-float transaction structures natively, and adapts when statement formats change — no manual mapping layer to maintain.
Time-series anomaly detection tuned to the rhythm of mobile-money flows — flagging the pattern that's genuinely unusual, whatever its size.
Ask a question about the data in plain language and get a grounded answer with the underlying transactions attached for verification.
| Data sources | M-Pesa statements and APIs, paybill/till reconciliation feeds, standard bank exports |
| Core capability | Anomaly detection, reconciliation, and natural-language querying over financial data |
| Deployment | Cloud-hosted with data-residency options, or on-premises for regulated clients |
| Integration | API access for embedding results into existing finance and ops tooling |