Legal Recruiting

Self-Service Placement & Market Intelligence for a Legal Recruiting Firm

Self-Service Placement & Market Intelligence for a Legal Recruiting Firm

4x

4x

Faster time from client question to answer

70%

70%

Reduction in manual data-pull requests to the operations team

About

The company places senior lawyers and partner-level teams at firms across the US, Asia, and Europe, and every placement decision depends on comparing compensation, book-of-business, and market-timing data that lived in scattered spreadsheets. We built a natural-language query layer over that data so recruiters get answers in seconds instead of waiting on a manual pull.

Industry

Legal Recruiting

Company size

10 – 50 employees

Founded

2016

The Company

A boutique legal recruiting firm competing on market intelligence

The firm is a global legal recruiting firm placing senior and partner-level attorneys at law firms and in-house teams across the US, Asia, and Europe. The firm's edge is depth of market knowledge — knowing which platforms are hiring, what comparable books of business have commanded in compensation, and when a lateral move makes sense for a given practice group.

That knowledge lived across placement records, compensation benchmarks, and market-timing notes accumulated over years, but accessing it for a specific client question meant a manual pull by the operations team rather than something a recruiter could do mid-conversation.

The challenge

Every client question meant a wait for a data pull

A recruiter on a call with a partner-level candidate needed to answer questions like "what have comparable books moved for in this practice area over the last 18 months" or "which platforms in this market have made a lateral hire like this recently." Answering meant pausing the conversation and waiting on the operations team to manually query historical placement records.

As the firm's placement history grew past 500 moves across four continents, the operations team's capacity to service these ad hoc requests became the bottleneck on how many live client conversations recruiters could carry at once.

The Solution

A natural-language query layer over the firm's placement history

We built a Text-to-SQL interface over the firm's placement and compensation database, letting recruiters type a question in plain English — "show me M&A partner moves in New York in the last two years with book size over $5M" — and get an accurate, structured answer with the underlying data visible for transparency.

The system was tuned to the firm's own terminology (practice groups, book-of-business bands, platform tiers) and included query validation with read-only access enforced at the infrastructure level, plus a saved-query function so recruiters could reuse their most common comparisons across client conversations.

The Results

4x faster answers and recruiters back in control of their own data

Time from client question to answer fell roughly 4x, with 92% of routine placement and compensation queries now self-served directly by recruiters rather than routed through operations. Manual data-pull requests to the operations team dropped 70%, freeing that capacity for the market-mapping and research work that genuinely needs it.

Recruiters reported being able to answer market-timing and compensation questions live, on the call, which changed the character of client conversations from "let me get back to you" to a real-time consultative discussion.

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ABOUT Seven Billion

Seven Billion is an Applied AI company — a team of data scientists and AI engineers who build and deploy AI systems that run in production. Founded in 2020. Offices in Boston, USA and Bengaluru, India.

OFFICE

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Bengaluru, India

The lowest-risk way to find out if AI is right for your business.

Whether you are mapping your first AI use case or scaling AI across the enterprise, we will help you cut through the noise and build something that actually ships.

ABOUT Seven Billion

Seven Billion is an Applied AI company — a team of data scientists and AI engineers who build and deploy AI systems that run in production. Founded in 2020. Offices in Boston, USA and Bengaluru, India.

OFFICE

Boston, USA
Bengaluru, India