Tech & Communications AI Use Case Ranking

Druva built DruAI, an agentic AI solution to help customers complete cyber investigations and recovery workflows.,The solution uses a multi-agent system on AWS with AgentCore Memory, AgentCore Code Interpreter, Amazon Bedrock access to Claude models, voice capabilities with Amazon Nova Sonic, and Bedrock Guardrails.,In production, DruAI coordinates 8 to 10 specialized agents across investigation, help, and recovery workflows.

Trend Micro enhanced its Companion AI assistant in its Vision One security software with long-term and short-term agentic memory capabilities.,The company used Amazon Neptune as a knowledge graph and experience layer to connect threat intelligence, alerts, investigations, and successful remediation patterns so analysts can get more explainable and personalized security recommendations.,Trend Micro combined Amazon Bedrock, Amazon Textract, and Amazon Managed Streaming for Apache Kafka to orchestrate agentic workflows, clean and enrich user conversations, and feed metadata into the graph for long-term memory and correlation analysis.

Ericsson describes an AWS-hosted rApp as a Service solution that uses agentic AI to automate RAN operations and optimization for communications service providers.,The platform integrates with Ericsson Intelligent Automation Platform and O-RAN interfaces to coordinate specialized agents for anomaly detection, root-cause explainability, cell shaping, and uplink performance optimization.,It is delivered as a multi-tenant SaaS offering through AWS Marketplace.

Fujitsu faced time-consuming and manual sales proposal creation processes, hampering staff productivity and slowing the onboarding of new salespeople. To address these challenges, Fujitsu developed an orchestrated multi-agent AI system using Microsoft Azure AI Agent Service, Azure AI Foundry, and Semantic Kernel, allowing them to automate data gathering and proposal drafting. The new system integrates with Fujitsu's existing workflows and leverages multiple specialized AI agents to dynamically retrieve, synthesize, and tailor sales proposals from dispersed enterprise data sources. As a result, Fujitsu boosted sales team productivity by 67%, enabling staff to focus on customer engagement, faster onboarding for new hires, and delivery of more accurate, data-driven, and current proposals.

Microsoft Build 2025 showcased the company's comprehensive strategy for developing the 'agentic web'—an ecosystem centered around the deployment of autonomous and multi-agent AI systems. Key announcements included Azure AI Foundry for multi-agent orchestration, next-generation GitHub Copilot coding agents capable of autonomous code refactoring and defect fixing, and Windows AI Foundry for local, on-device AI execution. Microsoft introduced new protocols for agent interoperability (A2A, MCP), enterprise-grade governance (Entra Agent ID), and advanced governance with Microsoft Purview integration. The standout real-world application, Microsoft Discovery, demonstrated the acceleration of scientific R&D—screening over 367,000 materials in 200 hours to rapidly develop a non-PFAS immersion coolant for data centers. The article illustrates a production-ready shift towards autonomous and multi-agent AI solutions, impacting software development, scientific research, and enterprise workflow automation.

Microsoft announced new Copilot Tuning and multi-agent orchestration in Microsoft 365 Copilot Studio, empowering organizations to build and fine-tune AI agents using domain-specific data, workflows, and processes. The low-code tools let non-data scientists create, deploy, and rapidly update custom AI agents. The release includes multi-agent orchestration, allowing agents to collaborate on complex cross-departmental workflows, such as onboarding and support, and integration with Azure AI Foundry so users can bring their models. Noteworthy customer examples: Wells Fargo reduced bankers' search time by 95% (10 min to 30 sec) via an agent serving 35,000 staff; T-Mobile uses agents to aggregate product data from over 20 sources instantly; HCLTech accelerated case resolutions by 40% and redeployed 30% of a 500-strong support team. Security and compliance are ensured via Microsoft Entra Agent ID and Microsoft Purview Information Protection. The ecosystem includes an Agent Store for discovery, a Teams AI library for multi-agent communications, and pro-code/low-code developer tools.

Adya is a tech company with two primary business segments: Adya, a SaaS-based data security platform that protects data in cloud applications, and Adya.ai, an AI-powered platform that transforms enterprise workflows into AI-powered agents and copilots, improving efficiency and driving cost savings.,The company built a platform on Google Cloud that combines Gemini, Vertex AI, Google Agentspace, Google Kubernetes Engine, Pub/Sub, Cloud Storage, and Virtual Private Cloud to support secure enterprise AI workflows.,The platform includes App Studio and Model Studio for AI-assisted application generation, fine-tuned LLM development, and configurable deployment options for enterprise customers.

Box builds customizable AI and AI agents with Google Cloud to democratize AI into workers' hands.,Box Agent and Box AI Studio let non-technical users create custom, purpose-built AI agents over Box content.,Agents authenticate to a company's Box instance and operate within existing user permissions and security settings.,Multi-agent systems use Agent2Agent (A2A) and Box MCP server to interact with other Gemini Enterprise agents.,BigQuery is used for reporting and processing structured aspects of unstructured data.

Quench.ai used Google Cloud to build a scalable, cost-effective AI platform for employees to search across company tools and data in seconds.,The company used Gemini 2.5 with Google AI Studio, Cloud Run, Cloud SQL, Memorystore, and Identity-Aware Proxy to prototype and deploy a custom debugging tool and other AI workflows.,Quench.ai says the platform enables faster access to internal information and supports agentic AI development for onboarding and handover scenarios.

Enterprises have long relied on Microsoft Entra’s Conditional Access policies to safeguard organizational resources, but manually managing these policies has proven complex and error-prone due to overlapping rules, legacy authentication risks, and rapid environmental changes. The Conditional Access Optimization Agent (CAOA), powered by Security Copilot and integrated within Microsoft Entra, addresses these challenges by continuously scanning user and app inventories, sign-in logs, and existing policies to identify unprotected users, risky applications, and policy gaps. The AI-driven agent analyzes data against Zero Trust principles and provides actionable recommendations with one-click remediation, reducing manual workload while empowering administrators with full oversight. Pilot organizations have already reported freeing up security team hours and discovering over 900 unprotected users not identified through manual audits. CAOA complements existing tools—such as the What If tool and Gap Analyzer—by automating policy reviews while maintaining robust audit trails for transparency. The tool requires Microsoft Entra ID P1+ and Security Copilot licenses and currently operates in private preview. Through proactive, AI-assisted policy management, organizations can both strengthen security and reduce operational overhead.

IBM faced major productivity drag across HR, procurement, IT, supply chain, sales, and tax because employees spent time searching for policies, navigating siloed systems, handling routine support, and manually aggregating data.,IBM set out to create an enterprise-wide productivity blueprint using AI, hybrid cloud, and automation, with domain assistants such as AskIT, AskHR, and AskSales deployed across workflows.

Totogi automates change request processing for telecom business support systems (BSS) with its BSS Magic platform.,The solution addresses the complexity of telco stacks that include hundreds of vendor applications and require costly customizations, lengthy testing, and specialized engineering expertise.,BSS Magic uses a telco ontology and a multi-agent framework to automate the full software development lifecycle for change requests, including business analysis, technical architecture generation, code generation, automated QA, and test suite generation.,Amazon Bedrock provides the foundation models, while AWS Step Functions and AWS Lambda coordinate state, orchestration, and workflow execution.

AIHelp provides AI-powered customer service to enterprise gaming customers in 32 countries and more than 40 languages.,The company adopted Google Cloud Vertex AI as a centralized MLOps platform and Gemini as the core LLM, with Vertex AI RAG/vector search, Translation AI, and Vertex AI Search to improve multilingual response quality and support agents.

Callers is a voice and text AI communications platform for B2C brands.,The company needed to scale fully autonomous AI agents across voice, SMS, chat, and WhatsApp while keeping latency low and response quality high.,Callers migrated infrastructure to Google Cloud, moved deployment to Google Kubernetes Engine, used Gemini as the core engine for natural-sounding voice conversations, and used Vertex AI for use-case-specific workflows.,The system maintains customer context across channels and routes insights back to clients' CRMs.

Galileo built an LLM reliability platform on Google Cloud to help customers de-risk, evaluate, and monitor generative and agentic AI applications.,The company uses Gemini, Vertex AI, Google Kubernetes Engine, Cloud SQL, Cloud Storage, Vector Search, BigQuery, and NVIDIA GPUs to run evaluation agents, multi-region deployments, and retrieval-augmented workflows.,The platform supports large-scale experimentation, model behavior measurement, and mitigation of hallucinations and other reliability issues for customer AI applications.

Siemens used Amazon Bedrock and Amazon Nova Foundation Models to streamline complex global search across 15-20 Siemens sites.,Customers can enter natural-language queries and receive relevant information in seconds, instead of sifting through marketing pages to find technical documentation.,An AWS Lambda function orchestrates validation, classification, summarization, and guardrail agents for the search workflow.

eSentire used Anthropic Claude in Amazon Bedrock to augment its managed detection and response security operations.,The system formulates investigation hypotheses from threat indicators, dynamically selects and executes evidence-gathering tools, and produces interactive investigation reports with evidence and reasoning chains.,The company validated model outputs against senior SOC experts and uses AWS services including Lambda, API Gateway, IAM, and CloudWatch to support the production workflow.

Verihubs is an Indonesia-based SaaS provider of digital verification and identity authentication services.,The company migrated to Google Cloud to support growing KYC demand, improve performance and cost efficiency, and prepare future AI-enabled workflows.,It also built an in-house deepfake detection capability to help identify AI-generated fraud attempts in images and videos.

Wonderful builds enterprise-grade AI agents that operate across voice, text, and email for customer service and internal workflows across multiple languages and markets.,The company uses Google Cloud to deliver low-latency multilingual interactions and to support rapid deployment and local adaptation for enterprise customers.

CANAL+ Group modernized its AWS environment to accelerate generative AI adoption for the myCANAL platform, including speech-to-text, natural-language search, and chatbot enhancements.,Working with AWS Training and Certification and AWS experts, the company built cloud skills, ran a hackathon for rapid proof-of-concepts, and applied guardrails for responsible generative AI.,CANAL+ also created an internal AI Factory for the Gender Equality Monitoring framework, using Amazon S3 and ML workflows to surface insights on gender representation.