LeadTable modernizes architecture to scale global search

THEIR CHALLENGE

Modernizing recruitment in the DACH region

In an employment market defined by fierce competition for talent and strict data regulations, LeadTable bridges the gap between recruitment agencies and a modern workforce. The Germany-based SaaS platform connects agencies with candidates by capturing leads through social media funnels and centralizing applicant data in a compliant, purpose-built dashboard. For a sector previously reliant on multiple email chains and unsecured spreadsheets, it brings structure, security and control.

As a fast-moving startup, LeadTable launched with MongoDB, choosing the data platform for its flexibility. "You can take some JSON, throw it in, and it will take it and not complain," said Michael Kirsch, CTO of LeadTable. In the early days, this allowed the team to prototype rapidly and ingest data from various sources without friction. However, as the platform’s popularity exploded, that same flexibility created complexities.

The core challenge was that every funnel provider—such as Meta Lead Ads, Perspective, and Funnel Cockpit—utilizes a unique data format. While one funnel might ask, "What is your name?", another simply prompts, "Name." Without a standardized structure in place, the team was forced to manually map these disparate fields to ensure the end user received a clean, consistent list. Eventually, the system began to struggle under the weight of this manual complexity and its rapid growth.

At first, LeadTable was able to patch inconsistencies in the front end, but ultimately couldn't withstand enterprise-grade "power users." When one leading insurance provider in Germany began processing upwards of 50,000 leads, LeadTable’s production server crashed. “That was not the greatest moment of my life,” said Kirsch with obvious understatement. It was a pivotal wake-up call: to support growth, LeadTable would need to fundamentally re-engineer its database strategy.

OUR SOLUTION

Strategic re-engineering with expert guidance

Confronted with what Kirsch described as a "big pile of tech debt," the LeadTable team realized that incremental fixes would no longer suffice. Having grown on a foundation of pure JavaScript and a schema that had become unfit for purpose, the platform’s technical limitations were stark: the team couldn't implement server-side pagination or generate accurate statistics. "There was no chance that we could make it work properly," Kirsch recalled. "We wanted to stop and rebuild it from scratch with TypeScript. That’s where we needed help, because we didn’t want to make the same mistakes again.”

To de-risk the new iteration, LeadTable partnered with MongoDB Professional Services, embedding a dedicated consultant, Divyanshu Verma, within its engineering team to guide architecture and execution. The goal was to handle tables with 30,000+ leads and achieve pagination in under 200 milliseconds.

The most significant hurdle was the "search everything" functionality of leads and applicant data across multiple collections. The existing architecture was fundamentally unsuited for the sheer volume and variability of the data being processed and performance had buckled as the platform tried to front-load all leads alongside the massive variety of custom funnel questions. "We need to make them all searchable, sortable, and countable quickly," said Kirsch.

Working in bi-weekly collaboration, MongoDB Professional Services helped the team navigate the complexities of indexing and data types. This was transformative. “We had misunderstood indexing,” admitted Pascal Brennich, Full Stack Software Developer, LeadTable. “MongoDB Professional Services not only helped us solve that, but made us understand how indexes work... that was a really valuable lesson."

While the team initially explored MongoDB Search on Atlas, they encountered unique constraints due to varied data types and initially sought a traditional indexing approach to stabilize the core. However, MongoDB’s expert guidance proved pivotal in eventually harmonizing their complex schema with the capabilities of MongoDB Search to enable agencies to query customers, logins, leads, and tables from a single, high-performance dashboard.

OUTCOME

A growth-ready platform built for global scale

By redesigning the schema for leaner collections and simplified relationships, LeadTable transformed from a functional product into a high-performance enterprise platform. The integration of MongoDB Search on Atlas delivered a "drop-in replacement" for its legacy RegEx search that was not only more accurate but exponentially quicker.

This architectural overhaul has yielded staggering improvements in precision and speed, with the team realizing a 95% improvement in search performance across more than 200,000 documents with MongoDB Search. The platform now delivers lightning-fast responsiveness, with global search latency plummeting from 1.5 seconds to just 70 milliseconds.

“By building a unified, materialized view, MongoDB Professional Services created the perfect structure for search,” said Kirsch. “Now our global search with MongoDB is insanely fast.”

This newfound efficiency has redefined LeadTable’s operational ceiling, enabling it to support recruitment agencies confidently and effectively. Instead of struggling to manually map unique data formats from diverse funnel providers, the infrastructure now seamlessly handles around 5 million requests per day and manages a total of 3.7 million leads.

By redrafting the codebase and architecting a properly functioning schema, the team has also successfully eliminated the “pile of tech debt” that once caused its production server to crash under the weight of enterprise power users. This shift has fundamentally changed LeadTable’s internal velocity, allowing its engineering team to “develop much faster” and bring structure, security, and control to the wider recruitment sector without fear of downtime.

Beyond the raw metrics, the partnership with MongoDB Professional Services has provided LeadTable with the technical confidence required to expand its footprint and the team is finally satisfied that their foundation is as ambitious as their business goals. "The work with DV and MongoDB Professional Services helped us to grow the product," said Brennich. "Now we are able to scale our traffic to expand internationally and overseas."

By unifying its highly scalable database and global search capabilities through MongoDB Atlas Search LeadTable is no longer just surviving growth—it is driving it.