Your Legal Invoice Data, Brought into Focus 

Aperture by Legal Decoder is a natural language interface for legal billing and spend data, built on Legal Decoder’s existing proprietary analytics foundation. Ask Aperture anything about your legal billing data and receive answers with full analytical depth in just seconds.  

THE INDUSTRY’S CHALLENGE

Legal invoice data is searchable. That doesn’t make it understandable.

Most legal analytics platforms can search invoices and UTBMS codes. That data is unstructured and doesn't answer what teams need to know.

UTBMS codes tell you where time was billed. They don't tell you which tasks drove cost, how work was staffed, or where efficiency broke down. Aperture reveals—in plain language—what actually happened at the matter level, not just how the time was coded.

QUERYABLE INTELLIGENCE

Ask more than your dashboards can answer.

Aperture is designed to help organizations and law firms navigate enormous amounts of legal billing and spend datasets with speed, transparency, and defensibility. Ask all of your burning billing questions and receive analyst-grade insights in seconds.

WHAT MAKES APERTURE UNIQUE

Anyone can add a Q&A layer. The advantage is what sits underneath.

Aperture combines conversational querying with Legal Decoder’s analytics foundation. Users aren’t analyzing raw invoices; they’re interrogating structured legal data.  

Before any data is queried, it is: 

Parsed

Invoice narratives and billing entries are broken into underlying components for analysis.

Categorized

Each activity is assigned the appropriate task and matter-level classification.

Enriched

Additional context is added to reveal the work performed, how it was staffed, and cost drivers.

Standardized

Inconsistent billing language is normalized into a consistent, comparable format.

Evaluated

The data is checked against compliance rules and analyzed for patterns, efficiency, and risk.

DATA PRIVACY

Tokenize, then Analyze

Before processing any data, Legal Decoder applies pre-LLM tokenization, replacing all identifying markers with secure tokens to protect sensitive information.

To the LLM, this data looks like a string of randomized characters, for example, “Matter_ABCDEF” rather than “M&A – Project Tycoon – 2026.” The AI can still process the language, analyze the metrics, and optimize workflows, but it has zero context regarding who the data belongs to.

Once the data is processed, results are remapped internally to restore business meaning inside Legal Decoder’s controlled environment.

Unlike traditional token vault architectures that maintain persistent mappings over time, Legal Decoder generates unique identifiers at the session level. This ensures the same underlying value is not consistently represented across tokenization runs.

Frequently Asked Questions

Ready to see the future of legal invoice review?

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