// 00Tag · ai agents

#ai agents

29 posts

AI agents: systems that do the work with tools — safely, behind an allow-list and a human-gate. From chatbot to an agent that acts.

18/06/2026

AI voice assistant for phone: replacing IVR with honesty

How a voice agent works in 2026 instead of IVR: STT-intent-TTS pipeline, latency budget, barge-in, Polish ASR, and the handoff threshold to a human.

18/06/2026

AI for in-house legal teams: contract review and RAG

By 2026, in-house legal departments are implementing AI for contract triage and obligation tracking. Check what can be realistically automated and what remains with the lawyer.

18/06/2026

AI for creating and maintaining technical documentation

How to keep wikis, runbooks, and API docs in sync with code in 2026: RAG over sources, drift detection, and the boundary automation never crosses.

18/06/2026

AI for detecting anomalies in corporate data: how it works in 2026

AI detects anomalies in transactions, logs, and metrics faster than static thresholds. What does this mean for your business in 2026, when humans make the final call?

17/06/2026

AI Agent with SQL Database Access: Safe text-to-SQL

How to deploy a text-to-SQL AI agent in 2026: schema-aware prompting, read-only guardrails, row limits, and human-gate for high-risk queries.

17/06/2026

Agentic RAG: an agent that plans searches autonomously

Agentic RAG in 2026: the agent plans queries, evaluates results, and decides when to escalate to a human. Is it worth replacing classic RAG with an agent-based approach?

17/06/2026

AI for banking and fintech: KYC, AML, risk, customer service

AI in banking and fintech 2026: KYC without paper stacks, AML with precision, credit risk with explainability. Where humans decide and why the AI Act is a requirement, not an option.

17/06/2026

AI for Controlling and Finance: OCR, Cost Analysis, and Month-End Close 2026

How AI supports controlling in 2026: invoice extraction, cost classification, variance analysis, and month-end close commentary. Hard rule: numbers are approved by the controller.

17/06/2026

AI for energy and utilities: forecasting, anomaly detection, documentation

AI in energy 2026: demand forecasting with honest accuracy ranges, sensor anomaly detection, documentation automation. What’s realistic, where human oversight is mandatory.

17/06/2026

AI for logistics and warehousing: demand forecasting, routing, and document automation

Real-world AI applications in logistics in 2026: demand forecasting with fair accuracy ranges, order routing, OCR for documents. Humans remain in the loop.

17/06/2026

AI for industrial manufacturing: predictive maintenance, quality control, documentation

AI in manufacturing 2026: predictive maintenance with sensors, image-based quality control, automated reporting. What's realistic and where human oversight is essential.

17/06/2026

AI for insurance: claims handling, document extraction, classification

AI in insurance 2026: data extraction from claims documents, claim classification, fraud signals, customer Q&A. Where human oversight is mandatory.

17/06/2026

AI for marketing teams: content drafts, segmentation, analysis — with oversight

AI for marketing teams in 2026: content drafts for human editing, segmentation, data analysis, and brand voice consistency. Where it helps and where human input is essential.

17/06/2026

AI for IT and DevOps teams: triaging, logs, and runbooks

How IT and DevOps teams use AI in 2026: alert triaging, log summarization, RAG on documentation, and the boundary an agent cannot cross.

17/06/2026

AI for sentiment analysis: from opinions to decisions

How AI turns thousands of reviews, tickets, and mentions into structured action signals in 2026. A practical pattern with human-gate and sample validation.

17/06/2026

AI for summarizing long documents: strategies and limitations

How AI summarizes contracts and reports longer than a single context window in 2026. Map-reduce, RAG with citations, and the boundary you shouldn’t cross without human oversight.

17/06/2026

AI in complaint handling: triage, response draft, and human-gate

How AI classifies complaints, detects sentiment and urgency, and prepares response drafts in 2026. Every substantive decision remains with humans.

17/06/2026

From AI pilot to production: what actually changes

What separates an AI demo from a production system in 2026: monitoring, guardrails, human-in-the-loop, costs, rollback, and SLA—and how to close this gap step by step.

01/06/2026

AI in logistics: warehouse, routing, and demand forecasting

How AI in logistics reduces warehousing costs, optimizes delivery routes, and predicts demand. Architecture, patterns, and limitations.

01/06/2026

AI for offer personalization and product recommendations

How to implement AI personalization and recommendations in a company: architecture, models, GDPR and AI Act, guardrails, costs, and when ROI begins.

01/06/2026

AI for translations in companies: how it works in practice

AI for translations in companies reduces the time for localizing documents, contracts, and marketing content. Architecture, quality, GDPR, and AI Act in one guide.

01/06/2026

AI in corporate education and training: a guide

How to implement AI in corporate training: personalized learning paths, knowledge agents, RAG on materials, GDPR and AI Act in practice.

01/06/2026

n8n and AI: end-to-end automations without coding

How to connect n8n with an AI model and build real end-to-end automation. Patterns, pitfalls, and secure integration principles.

01/06/2026

AI Agent Maintenance Costs: TCO and Operations

AI agent maintenance costs in TCO terms: infrastructure, tokens, monitoring, knowledge base updates, and human oversight. What does an agent really cost after deployment?

01/06/2026

MCP: how AI securely connects to tools

MCP (Model Context Protocol) is an open standard for connecting AI models to external tools and data. How it works, what it offers businesses, and what security risks it entails.

01/06/2026

Monitoring and KPIs for AI Agents: How to Measure Effectiveness

How to monitor an AI agent, which KPIs make business sense, and how to build a quality dashboard before deployment spirals out of control.

01/06/2026

No-code (Make, Zapier) vs custom AI agent

When Make and Zapier are enough, and when do you need a custom AI agent? Comparison of capabilities, costs, and limitations of no-code vs dedicated architecture.

01/06/2026

Multi-agent systems in a company: when to use them and how to connect them

AI multi-agent systems 2026: when orchestrating multiple specialized agents outperforms a single overloaded one and how to avoid loops, costs, and chaos.

01/06/2026

Multilingual AI assistant: customer service in multiple languages

A multilingual AI assistant serves customers in their own language without separate bots per language. Architecture, language detection, guardrails, and GDPR in practice.

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