What happened
Tradeshift, an AI-powered accounts payable platform serving over 70 countries, migrated from a proprietary in-house BI tool to Amazon Quick (an agentic AI workspace with chat, workflow automation, and research capabilities). The rollout began with a proof of concept in early 2024, launched a full Reporting and Analytics app in June 2025, and by August 2025 achieved 98 percent adoption across the organization.
Why it matters
The legacy tool's constraints—10,000-row query limit, 25 MB report ceiling, six-month data retention, 50 percent of one full-time employee's maintenance burden—blocked large-scale analytics, forced manual reporting bottlenecks, and locked customers out of self-service insights. Amazon Quick eliminates those constraints and lets both internal teams and external customers ask questions in plain language without SQL expertise, turning embedded analytics into a revenue-generating product feature.
What to watch
Tradeshift achieved measurable gains: query response times dropped from 45–90 seconds to under three seconds; a 40 percent reduction in total cost of ownership; internal teams saved 8.5 hours per week on manual reporting; external users saved 6–8 hours per week per user; 2 percent incremental annual recurring revenue expansion from the premium tier; and 75 percent faster time-to-market for custom enterprise reports (now ~one week, down from 4–6 weeks).
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Tradeshift's migration reflects a broader shift from monolithic, code-heavy business intelligence tools to conversational, agentic AI platforms that lower barriers to data access. The legacy in-house tool, while appropriate for early-stage operations, became a drag on growth: its technical constraints (10,000-row limit, six-month retention) made large-scale analytics impossible, its maintenance burden consumed engineering capacity that could have fueled product innovation, and its lack of self-service interfaces forced customers and internal teams into dependency bottlenecks. Manual reporting—CSV exports, Excel macros, hand-assembled dashboards—consumed 8.5 hours per week for internal teams and 6–8 hours per week for each external customer, creating friction that delayed decision-making on both sides.
Amazon Quick's agentic capabilities—chat agents that interpret natural language, workflow automation (Flows) that orchestrates recurring tasks without code, and research engines (Research) that synthesize multi-source analysis—directly addressed these pain points. The platform's architecture also enabled Tradeshift to turn analytics into a customer-facing product: a tiered model (Standard for pre-built dashboards, Premium for custom creation and what-if modeling) converted what was once an internal cost center into a source of incremental annual recurring revenue (2 percent ARR expansion from existing buyer accounts in the first year). By August 2025, 98 percent of Tradeshift's organization actively used the platform, and accounts using embedded analytics showed 10 percent higher retention over 12 months.
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