Wholesale and roaming bills do not fail because nobody can count. They fail because usage records, partner invoices, and contract rates disagree—and someone has to prove which side is wrong.
CDR or usage feeds, partner invoices, and rate decks live in different systems. Analysts export spreadsheets, match on partial keys, and open disputes by email with a pile of sample records.
Volume is high and variance is normal. The hard part is not spotting a single mismatch; it is deciding which mismatches are material, which are timing, and which need a formal dispute package.
When a dispute closes, the trail is often scattered: the original export is gone, the rule that flagged the row is forgotten, and the next quarter starts from zero.
We build reconciliation agents that ingest usage and invoice data on a schedule, apply partner-specific matching rules, classify variances, and open dispute cases with evidence attached—not a one-off spreadsheet.
Matching is mostly deterministic: keys, windows, and rate lookups from your contracts. Models help where free-text memo fields or non-standard invoice layouts need interpretation—with confidence scores and human review when uncertain.
Settlements and write-offs stay with finance or partner management. The system owns the match, the queue, and the audit path.
Sense: pull usage extracts, partner invoices, and rate tables from the mediation or billing stack; normalize into a reconciliation schema.
Reason: run partner-specific match rules; score residuals by amount and count; draft dispute packages for thresholds you define.
Rock: write results to a case system or finance queue; notify partner managers; retain match logs and source row IDs for the dispute window.
Fuzzy matching without a versioned rule set. When a partner format changes, you need a change you can review—not a prompt that drifted last Tuesday.
Auto-closing small variances without a materiality policy. Noise either floods the queue or hides real leakage.
No link back to source CDRs. A dispute without reproducible samples dies in partner negotiations.
It is a system that matches usage or interconnect records against partner invoices and rates, flags material variances, and prepares dispute evidence. Agents execute the match and packaging; finance owns settlements.
Mediation prepares usage for billing. Reconciliation checks whether what you billed or were billed matches contract and traffic. We often sit downstream of mediation and billing, wired into partner invoice formats you already receive.
No. Rates come from your rate deck or contract tables. Missing usage is a finding, not something the model fabricates. Interpretation is limited to document layout and memo fields under schema validation.
Each partner gets a matching profile: keys, time windows, tolerances, and invoice parsers. New partners start from a template; they do not all share one fragile prompt.
One partner group, one product (e.g. roaming or a single interconnect), scheduled runs, a variance queue, and dispute packs your team can send without re-exporting raw files by hand.
Engineering services
Telecom billing and dispute reconciliation is the kind of workflow we build as an AI agent system: deterministic checks, human checkpoints, and an audit trail operators can trust. We start from your real process boundaries and ship software that holds up in production.
We build production-ready, highly observable agentic systems engineered for enterprise scale. No black boxes, no magic—just systematized workflows with systemic safeguards.
We don't build fragile wrappers. Complex decisions and exceptions are automatically routed to your team for approval, ensuring zero unverified actions in production.
Every AI-generated output is validated against deterministic, programmatic rules before execution, guaranteeing structural integrity and compliance.
Our architecture records every state change, agent reasoning step, and user interaction, providing complete observability into your automated workflows.
Built for enterprise scale. We optimize for high-throughput, low-latency execution using edge infrastructure and efficient state management.
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