Overview
Sapience Analytics provides workforce intelligence software that helps enterprise organisations optimise productivity, collaboration, and workplace efficiency. A core part of their platform relies on ingesting and processing large volumes of meeting data. Sapience had designed integrations using the Cyclr iPaaS Solution.
As Sapience’s enterprise customer base grew, the performance and reliability of these integrations became increasingly critical. Long-running integrations, inconsistent failures, and incomplete data batches began to impact analytics delivery for enterprise customers. Cyclr introduced James Chase to Sapience such that James Chase could work with Sapience to optimise their integration design.
James Chase’s engagement centred on the need to stabilise and optimise Sapience’s integration designs, improving performance, eliminating recurring failures, and ensuring the integrations were optimised to operate reliably in live enterprise environments.
The Challenge
Sapience had already adopted Cyclr as the orchestration layer for batching and processing high volumes of meeting data from Microsoft Teams and Google Meet. However, increasing scale exposed deficiencies in the integration workflows that had been designed within the Cyclr tooling.
As data volumes increased, integration runtimes were extending beyond acceptable processing windows. Inconsistent metadata for bots, guests, and external users regularly triggered API errors, and in some cases, single node failures could cascade across entire cycles.
These issues directly impacted enterprise customers and placed pressure on internal support teams. All improvements needed to be delivered quickly, safely, and in close collaboration with Sapience’s in-house engineers, with no tolerance for disruption to production systems.
The Solution
James Chase carried out a detailed technical review of Sapience’s integration flows to identify bottlenecks, inefficient execution paths, and recurring failure patterns. We restructured key integrations to improve throughput, resilience, and data completeness.
This involved reducing unnecessary Microsoft Graph API calls, improving batching strategies, and introducing more efficient branching logic. Identity-type filtering and fallback handling were implemented to ensure bots, guests, and external users were processed correctly, preventing edge cases from causing failures.
Error handling was strengthened so that individual node issues could no longer collapse entire batches, transforming the integration suite into a stable, enterprise-ready pipeline. Delivery was coordinated across teams in India, Vietnam, and Nigeria, enabling rapid iteration despite time pressure and production sensitivity.
The Impact
The optimised integration designs delivered immediate and measurable improvements for Sapience Analytics:
• 40% reduction in overall integration runtime
• Near-zero daily errors across Teams and Google Meet integrations
• Predictable 24-hour ingestion cycles at enterprise scale
• Complete and accurate processing of all meeting participants and activity
• Reduced operational support effort and fewer customer escalations
Sapience now operates a clean, reliable Cyclr-powered integration layer that underpins its enterprise analytics platform and provides a scalable foundation for continued growth.
Interested in similar results?
Email or call at:
steve.rackley@james-chase.com
01273 355141