Anthropic Claude can support software testing by generating test scripts, analyzing requirements, creating test scenarios, interpreting application behavior and assisting QA teams with repetitive testing tasks. Claude Haiku is well suited to high-volume, low-latency test generation, while Claude Sonnet and Opus can support more complex reasoning and assurance use cases. Inflectra used Claude across its QA ecosystem with Merito’s AI systems integration expertise, achieving roughly 90% time savings in Rapise test-script creation. Merito helps enterprises evaluate, integrate, implement and optimize Claude for enterprise QA automation.
Merito accelerates Inflectra's AI-powered QA transformation with Claude
Inflectra, working with Merito, a software quality assurance and application lifecycle management company, deployed Anthropic Claude models across its flagship products and internal R&D workflows. Merito as their AI systems integrator helped designed a multi-model Claude architecture on Amazon Bedrock that now powers automated testing in Rapise, AI assurance in SureWire, and internal engineering workflows in Amazon Kiro, cutting test-script creation time by as much as 90%.
With Merito and Claude, Inflectra was able to:
- Deploy Claude Sonnet, Haiku, and Opus across Rapise, SureWire, and internal R&D, all running inside Inflectra's own Amazon Bedrock accounts
- Cut test script creation in Rapise from hours of manual scripting to seconds, using Claude Haiku for high-speed, cost-efficient generation
- Replace manual, error-prone compliance auditing with automated risk and assurance mapping in SureWire, powered by Claude Opus and Sonnet
- Lift internal developer velocity 30%+ on code generation and documentation through Amazon Kiro
- Build a task-complexity-based model routing layer that holds sub-second latency while optimizing cost-per-token across every product surface
- Use Claude's text, visual processing, and computer-use capabilities to bring AI assurance to non-deterministic, agentic systems, not just traditional scripted software
The Challenge:
Inflectra needed to rapidly embed advanced, enterprise-grade AI capabilities into its flagship products SpiraPlan, Rapise, and SureWire, to keep pace with rising demand for AI-driven software development lifecycle (SDLC) management. The company also wanted to inject AI efficiencies into its own internal development workflows via Amazon Kiro.
The complexity sat beneath the surface. Infusing three distinct Claude models: Sonnet, Haiku, and Opus, across a mix of legacy and modern architectures required specialized prompt engineering, model-routing optimization, and integration work that Inflectra needed done quickly and without pulling engineers off the core product roadmap.
The Solution:
Merito stepped in as Inflectra's expert systems integrator and AI services partner, bringing deep hands-on experience with Anthropic's model ecosystem. Rather than treating Claude as a single drop-in model, Merito architected a routing layer that sends each task to the most efficient model for its complexity: Haiku for high-speed, cost-effective generation; Opus and Sonnet for the reasoning-heavy work of AI assurance.
The Outcome:
The collaboration delivered measurable improvements in software delivery speed, test automation accuracy, and internal developer velocity across Inflectra's product suite.
Metric | Before Merito & Anthropic | After Merito & Anthropic |
Test automation generation (Rapise) | Manual script creation taking hours | Claude Haiku generates test scripts in seconds, roughly 90% time savings |
AI assurance & compliance (SureWire) | Manual, error-prone compliance auditing | Automated, high-accuracy risk and assurance mapping via Claude Opus and Sonnet |
Internal dev velocity (Amazon Kiro) | Standard sprint cycles for product R&D | 30%+ boost in internal code generation and documentation using Claude |
Model efficiency & cost | Unoptimized API usage and latency risk | Multi-model routing optimizing cost-per-token while holding sub-second latency |
Taken together, the engagement let Inflectra move from manual, labor-intensive QA and compliance processes to an AI-native architecture that scales with demand, without diverting its own engineers from the product roadmap.
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