Blog
An AI Agent for Missed WhatsApp Enquiries
Enquiries arrive on WhatsApp at all hours, as photos, in different languages. An agent connected to the ERP reads them and replies with real sizes, prices, and stock. Building this in-house takes months; the capability already exists.
An AI Agent for Missed WhatsApp Enquiries
Enquiries arrive on WhatsApp at all hours, as photos, in different languages. An agent connected to the ERP reads them and replies with real sizes, prices, and stock. Building this in-house takes months; the capability already exists.
An AI Agent for Machine Downtime Pattern Detection
An AI agent that reads stoppage logs across machines, groups them by cause, and flags a recurring downtime pattern before the next breakdown, with a maintenance engineer confirming the cause.
An AI Agent for Quote and Discount Authorization
An AI agent that checks a drafted quote against the approved rate card and discount floor and flags anything below it, with the owner or sales head clearing every exception before it reaches a customer.
An AI Agent for Raw Material Wastage Tracking
An AI agent that checks material issued against a batch's standard consumption and flags the gap while the batch is running, with a production supervisor confirming the cause before it's logged as wastage.
An AI Agent for Payment and Outstanding Tracking
An AI agent that checks outstanding invoices against payment terms and drafts the reminder before a payment is overdue, with an accounts person approving and sending every message.
An AI Agent for Dispatch and LR Tracking
An AI agent that checks the dispatch log and LR record against the delivery promise and drafts the status reply a dealer is asking for, with a dispatch clerk approving and sending every message.
WhatsApp Automation for Business: How an AI Agent Handles It
WhatsApp automation for a business is not a chatbot, and Mirai360 is not a WhatsApp tool — it's an AI layer for one specific business workflow (photo-to-quote, order status, or follow-ups), reached through WhatsApp, with a named person approving every message before it sends.
Build or Buy? The Three-Condition Test Before You Fund an AI Team
Building AI in-house only pays off when three conditions hold at once: volume, patience, and bench. Missing any one produces a specific, predictable failure. A framework to test your case before you fund a team.
Agentic AI in Manufacturing: Vision Agents for Assembly, Safety, and Paperwork
Three shop-floor workflows where computer vision already does useful work: assembly and process verification, safety and PPE compliance, and document OCR. In each, a vision model detects, an agent drafts the next step, and a named person approves it.
AI Agents for Tile Manufacturers: From WhatsApp Photo to Quote
In Gujarat's tile cluster, most enquiries start with a photo on WhatsApp. This post explains how an AI agent matches that photo to a manufacturer's own catalogue and drafts a quote, with a person approving every quote before it sends.
Why Multi-Agent Orchestration Matters, and Why Defence Is the Proof
Agentic AI projects fail on orchestration, not models: agents run with no defined authority, no audit trail, and no human checkpoint. This post explains the multi-agent orchestration layer, why published defence-AI doctrine is its clearest specification, and how Vajra, Mirai360's defence platform, proves the same architecture that runs our commercial deployments.
Agentic AI in Retail: Replenishment, Returns, and Customer Service
Retail runs on queues that never empty: customer questions, reorders, returns, price reviews. This post explains which retail workflows fit AI agents first, why a person stays on every decision that moves money or inventory, and the discipline that keeps a deployment out of the 40% of agentic AI projects Gartner expects to be cancelled by 2027.
How an AI Agent Handles Maintenance Scheduling
An AI agent builds and adjusts a preventive-maintenance schedule, triages breakdown tickets by urgency, and drafts spare-part orders for a supervisor to approve. How manufacturing leaders control the rollout: a measured baseline, authority boundaries, an audit trail, and scale decided on pre-agreed numbers.
AI Agent for Order-Status and Delivery Support: How It Works
Mirai360's order-status agent reads the ERP, drafts a reply, and escalates exceptions to a person. A measured baseline before deployment, a human on every exception, and a full audit trail keep the workflow accountable.
AI Agent for Quality-Inspection Triage in Manufacturing
Mirai360 builds an AI agent that reads inspection reports, triages non-conformances by severity, routes them, and drafts the first version of a CAPA note. A quality engineer approves every disposition.
How an AI Agent Handles Inventory and Procurement
An AI agent watches stock levels and consumption, forecasts reorder points, and drafts purchase orders for a buyer to approve. How manufacturing leaders control the rollout: a measured baseline, authority boundaries, an audit trail, and scale decided on pre-agreed numbers.
AI Agents for RFQ and Quote Generation in Manufacturing
For a mid-size manufacturer, a slow RFQ response can cost an order before pricing is even wrong. This use case explains how an AI agent drafts RFQ responses from a spec sheet, pricing rules, and past quotes, with a person approving every quote before it goes out, and how Mirai360 AI applies its deployment discipline to keep that authority in the shop's hands.
The Value Gap: 88% Use AI, Only 6% Make Money From It
88% of organizations use AI in at least one business function. Only about 6% clear McKinsey's bar for an 'AI high performer': attributing more than 5% of EBIT to AI. The gap between adoption and profit is a measurement problem, not a technology one.
Agent-Washing: Only ~130 of Thousands of AI-Agent Vendors Are Real
Gartner: only ~130 of thousands of self-described agentic-AI vendors offer genuine agentic capability. Most of the rest are rebranded chatbots or RPA. A vendor-diligence checklist and kill thresholds to set before you sign.
Klarna Replaced 700 Agents' Worth of Work, Then Rehired Humans
Klarna's AI assistant handled 2.3 million chats in a month, equal to ~700 agents' workload. By mid-2025 it was rehiring humans. The CEO's own words on why, and the triage pattern that fixed it.
Shadow AI: Why Your Team Is Pasting Contracts Into ChatGPT
Employees are already pasting contracts, quotes, and client data into ChatGPT and Claude. The data on how much confidential material is moving through consumer AI, and what a controlled alternative looks like.
What an LLM gateway is, and why your business should care
A plain-language explanation of what an LLM gateway does, and why it protects a business from vendor lock-in, cost surprises, and outages.
What is an agentic AI platform? A business operator's guide
A plain-language guide for business owners on what an agentic AI platform does, why it differs from a chatbot, and how to evaluate one.
Three paths to AI agents in production: self-hosted, managed, custom-built
A comparison of the three ways a business can put an AI agent into production: self-hosted, managed, or custom-built by a services team.
Privacy-first AI: why running agents in your own cloud matters
Why businesses should run AI agents in their own cloud: data control, client trust, compliance, and exit freedom explained for business operators.
Inventory and accounting agents: books that are always current
How AI agents keep stock records and accounting books continuously up to date, and what SME owners gain from books that never fall behind.
Evals and guardrails: how to trust an AI agent with real work
What evals and guardrails are, how they differ, and why both are required before a business lets an AI agent handle real work.
From digital transformation to intelligence transformation
Why the next business upgrade cycle is not another software rollout, but giving existing systems the ability to reason and act.
AI agents for quotes and follow-ups: the fastest return for an SME
Why quoting and follow-up work is the first place an SME should deploy AI agents, what an agent actually does, and how to start without hiring engineers.
What agentic AI platforms change for law firms
How agentic AI platforms change law firm operations: intake, document review, drafting support, and matter administration, with confidentiality intact.
Agentic AI in insurance: intake, claims triage, and audit trails
How agentic AI handles insurance intake and claims triage while producing the audit trails regulators and reinsurers expect.
The Governance Gap: ~79% of Organizations Cannot Govern Agentic AI
Only 21% of organizations have mature agentic AI governance — meaning ~79% do not. What's missing, and why writing the control document early is what makes speed survivable.
Most Agentic AI Projects Being Built Right Now Will Not Survive
Gartner forecasts 40%+ of agentic AI projects canceled by end-2027 — escalating costs, unclear business value, inadequate risk controls. Three questions to ask before you build.
The Scaling Gap: Only 23% of Organizations Are Scaling Agentic AI
88% of organizations use AI somewhere. Only 23% are scaling an agentic AI system anywhere. Why the gap is organizational, not a model problem.