# self-service

Self-service is a computing concept in which consumers can automatically provision computing capabilities, such as server time and network storage, without human interaction with the service provider.

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## How MRH Trowe enabled secure self-service AI agents in financial services

DevFeed: [How MRH Trowe enabled secure self-service AI agents in financial services](<https://devfeed.tech/articles/how-mrh-trowe-enabled-secure-self-service-ai-agents-in-financial-services-42131.md>)

Original publisher: [Read original article](<https://aws.amazon.com/blogs/machine-learning/how-mrh-trowe-enabled-secure-self-service-ai-agents-in-financial-services/>)

Author: Marouane El Bostahi

Published: 2026-09-17T15:36:42Z

Content type: article

Language: en

Sources: [Artificial Intelligence](<https://devfeed.tech/sources/artificial-intelligence.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Amazon Bedrock AgentCore](<https://devfeed.tech/topics/amazon-bedrock-agentcore.md>), [Strands Agents](<https://devfeed.tech/topics/strands-agents.md>), [self-service](<https://devfeed.tech/topics/self-service.md>), [Security](<https://devfeed.tech/topics/security.md>), [data](<https://devfeed.tech/topics/data.md>), [Cloud](<https://devfeed.tech/topics/cloud.md>), [scaling](<https://devfeed.tech/topics/scaling.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-agents](<https://devfeed.tech/tags/ai-agents.md>), [amazon-bedrock-agentcore](<https://devfeed.tech/tags/amazon-bedrock-agentcore.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [customer-solutions](<https://devfeed.tech/tags/customer-solutions.md>), [financial-services](<https://devfeed.tech/tags/financial-services.md>), [security](<https://devfeed.tech/tags/security.md>), [self-service](<https://devfeed.tech/tags/self-service.md>), [strands-agents](<https://devfeed.tech/tags/strands-agents.md>)

### AI overview

This AWS case study describes how MRH Trowe provided about 400 employees with secure, self-service AI agents during its first month of production. The solution combines Strands Agents, Amazon Bedrock AgentCore, and LibreChat to support security, data residency, compliance, and cost transparency in the German financial sector.

### Source excerpt

Learn how MRH Trowe, one of Germany's leading commercial and industrial insurance brokers, gave about 400 employees secure, self-service access to AI agents in its first month of production - using Strands Agents, Amazon Bedrock AgentCore, and LibreChat to meet the security, data residency, and compliance requirements of the German financial sector.

## From COBOL to Copilot: 30 Years of Data, BI, and AI with David Langer

DevFeed: [From COBOL to Copilot: 30 Years of Data, BI, and AI with David Langer](<https://devfeed.tech/articles/from-cobol-to-copilot-30-years-of-data-bi-and-ai-with-david-langer-38709.md>)

Original publisher: [Read original article](<https://dataengineeringcentral.substack.com/p/from-cobol-to-copilot-30-years-of>)

Author: Daniel Beach

Published: 2026-07-01T13:43:11Z

Content type: article

Language: en

Sources: [Data Engineering Central](<https://devfeed.tech/sources/data-engineering-central.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [cobol](<https://devfeed.tech/topics/cobol.md>), [Data Science](<https://devfeed.tech/topics/data-science.md>), [mainframes](<https://devfeed.tech/topics/mainframes.md>), [Software Engineering](<https://devfeed.tech/topics/software-engineering.md>), [AI Strategy](<https://devfeed.tech/topics/ai-strategy.md>), [self-service](<https://devfeed.tech/topics/self-service.md>), [dashboards](<https://devfeed.tech/topics/dashboards.md>), [jupyter notebooks](<https://devfeed.tech/topics/jupyter-notebooks.md>)

Tags: [adoption](<https://devfeed.tech/tags/adoption.md>), [ai](<https://devfeed.tech/tags/ai.md>), [business-intelligence](<https://devfeed.tech/tags/business-intelligence.md>), [cobol](<https://devfeed.tech/tags/cobol.md>), [data-science](<https://devfeed.tech/tags/data-science.md>), [enterprise](<https://devfeed.tech/tags/enterprise.md>), [jupyter-notebooks](<https://devfeed.tech/tags/jupyter-notebooks.md>), [mainframes](<https://devfeed.tech/tags/mainframes.md>), [programming](<https://devfeed.tech/tags/programming.md>), [self-service](<https://devfeed.tech/tags/self-service.md>), [semantic](<https://devfeed.tech/tags/semantic.md>)

### AI overview

A podcast conversation with Dave Langer about nearly three decades spanning COBOL, enterprise architecture, business intelligence, analytics, data science, machine learning, and AI. It discusses persistent data-industry problems, self-service analytics, dimensional modeling, AI adoption, semantic layers, governance, and career advice for data professionals.

### Source excerpt

What happens when someone who started programming on a Commodore 64 watches AI reshape the entire data industry?

## Threat Modeling with Questionnaires

DevFeed: [Threat Modeling with Questionnaires](<https://devfeed.tech/articles/threat-modeling-with-questionnaires-37055.md>)

Original publisher: [Read original article](<https://shostack.org/blog/threat-modeling-with-questionnaires/>)

Author: Adam

Published: 2020-03-19T00:00:00Z

Content type: article

Language: en

Sources: [Shostack & Friends Blog](<https://devfeed.tech/sources/shostack-friends-blog.md>)

Topics: [Application Security](<https://devfeed.tech/topics/application-security.md>), [Security](<https://devfeed.tech/topics/security.md>), [self-service](<https://devfeed.tech/topics/self-service.md>), [sensitive data](<https://devfeed.tech/topics/sensitive-data.md>)

Tags: [appsec](<https://devfeed.tech/tags/appsec.md>), [security](<https://devfeed.tech/tags/security.md>), [self-service](<https://devfeed.tech/tags/self-service.md>), [sensitive-data](<https://devfeed.tech/tags/sensitive-data.md>)

### AI overview

The article examines lightweight threat modeling through self-service security questionnaires. It argues that developers or scrum masters can identify what they are building, what could go wrong, and whether security engineers should focus on the feature based on its risk.

### Source excerpt

This post comes from a conversation I had on Linkedin with Clint Gibler.