Faster feature deployment

Bito implemented AI-powered developer agents by integrating Anthropic's Claude and leveraging Claude 3.7 Sonnet for advanced reasoning into its code review and coding workflows. They utilized Anthropic’s robust API and developer-friendly infrastructure to embed an AI Code Review Agent and Bito Wingman directly within developers’ Git workflows and popular IDEs, enabling automated analysis of pull request diffs and code architecture. This integration streamlined code review, error detection, and code generation processes while upholding security standards.

Augment code integrated Anthropic's Claude within Google Cloud's Vertex AI to develop an AI-powered code assistant that provides expert-level contextual understanding of complex software systems. By automating code comprehension, debugging, documentation, and change propagation within development workflows, the solution dramatically reduced project timelines and sped up developer onboarding while ensuring SOC 2 Level 2 compliant security protocols.

Tata Elxsi integrated Microsoft GitHub Copilot into its video distribution platform development and testing processes to provide intelligent code suggestions, optimize existing code, assist in both manual and automated testing, simplify documentation, and enable smoother code translation. The integration streamlined coding and debugging workflows across the development cycle, enhancing productivity and ensuring compliance with strict security standards.

Cox Automotive integrated Claude via Amazon Bedrock into its portfolio by first creating a sandbox environment to evaluate performance metrics and then selecting Claude 3.5 Sonnet for complex tasks and Claude 3.5 Haiku for high-volume content generation. They automated personalized dealer-consumer communications, generated engaging vehicle listing descriptions, and produced SEO-optimized blog posts, while also streamlining internal data governance through automated metadata generation. This integration optimized operational efficiency across marketing and internal data processes.

Quillit integrated Anthropic’s Claude to automate qualitative research tasks by summarizing interview transcripts, generating contextual citations, and threading conversation data into comprehensive reports. They implemented the AI tool into their existing research workflow within three months, streamlining report writing, transcription, and analysis while ensuring data security and high precision.

Block implemented Anthropic’s Claude models (Claude 3.5 Sonnet and Claude 3.7 Sonnet) on its Databricks platform to power its internal AI agent, codename goose. They integrated the LLM using secure OAuth-enabled connections and a custom MCP server to connect internal databases and tools, enabling employees across all roles to auto-generate SQL queries, analyze complex data, and automate workflows. This agentic integration streamlined software development, design prototyping, and data analysis by translating user intents into actionable insights.

Deutsche Bank developed DB Lumina, an AI-powered research agent built on Gemini and Vertex AI through a partnership with Google Cloud. The solution automates the creation of financial research reports by rapidly condensing extensive market data—such as converting a 400-page report into a three-page summary—thereby streamlining analysis workflows while maintaining rigorous data privacy standards.

Capgemini partnered with Google Cloud to develop industry-specific agentic AI solutions that automate customer request handling across multiple channels such as web, social, and phone. The implementation integrates Google Agentspace, Customer Engagement Suite, and Agent2Agent interoperability protocol into existing customer service infrastructures to enhance personalized support, call routing, and workflow automation. This advanced solution transforms customer experience by streamlining communications and enabling proactive engagement.

wealthAPI implemented a next‐gen contract detection solution by integrating DataStax Astra DB on Google Cloud and leveraging Google Gemini models for AI‐powered analysis. They deployed DataStax’s vector search and real‐time insights capabilities to scale contract detection across millions of users in less than three months, streamlining wealth management workflows by dramatically reducing response times and efficiently handling massive data volumes.