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Founder, IKAG

Ronit Ahuja

Ronit Ahuja is the founder of IKAG (I Know A Guy). IKAG is building one connection that gives the AI apps and agents people already use the paid tools and data they can’t reach on their own, paid per call instead of a subscription to each service, with each result returned with where its data came from.

Ronit writes about AI agents and the data they reach: how agents choose sources, what a source record should contain, how to report unknowns honestly, and what the Model Context Protocol does and does not standardise. Posts draw on real lookups made by IKAG’s first capability, company legal identity from official registries.

  • AI agents
  • Model Context Protocol
  • Data provenance
  • Legal Entity Identifier
  • SEC EDGAR
  • Agent infrastructure

Articles by Ronit Ahuja

  1. 5 min read Subscription fatigue: paying for tools you use twice Subscription fatigue in numbers: firms leave 36% of software licences unused on average, and UK consumers spend 1.6 billion pounds a year on unwanted subscriptions.
  2. 6 min read Bulk AI video without a subscription: what to know How AI video is sold in 2026, from monthly credits to per-second API pricing, how to make 20 ad takes without a plan, and the quality, rights and labelling checks.
  3. 6 min read ChatGPT Dots, Grok Bot and Meta Muse explained ChatGPT Dots, Grok Bot and Meta’s Muse are AI agents with their own cloud computers. What each one does, who can get it and what none of them can reach.
  4. 7 min read Do you need a subscription for every AI tool? Not one per AI app: a single account at a service can work in ChatGPT, Claude and Cursor. What adds up is a subscription to each service your AI uses.
  5. 5 min read How AI agents find B2B leads, and what to check Where an AI agent’s list of businesses and decision makers comes from, why models alone get work emails wrong, the UK and US email rules, and what a good list includes.
  6. 5 min read How to add a tool to ChatGPT, Claude and Gemini Step by step: add a custom connector or MCP server in ChatGPT, Claude, Gemini, Cursor, VS Code, Claude Code and Codex, with plan limits as of October 2026.
  7. 5 min read Local business data for AI agents: sources and rules How an AI agent can list local businesses with ratings, reviews, websites and opening hours: map platforms, open data and business websites, their terms and freshness.
  8. 6 min read Pay per call vs monthly plans for AI tools Monthly plans suit steady use and pay per call suits bursts. How they compare for AI tools: quotes before a call, spending limits, receipts and your own keys.
  9. 5 min read What is MCP? A plain-English guide for AI users MCP, the Model Context Protocol, lets ChatGPT, Claude, Gemini and other AI apps use outside tools. What it is, how connecting works and how to stay safe.
  10. 3 min read Do AI summaries send people to their sources? Pew Research found Google users clicked a result in 8% of visits with an AI summary and 15% without. What that means for answers you need to check.
  11. 4 min read How to look up a company’s LEI with an AI agent What a Legal Entity Identifier is, how an AI agent should query the GLEIF register, and why “no match” or “lapsed” never means a company is gone.
  12. 3 min read LEI, CIK or Wikidata ID: which company identifier? A practical guide for agents and developers: what LEIs, SEC CIKs and Wikidata IDs identify, who issues them, how to resolve each, and when to link them.
  13. 4 min read Tool routers and data networks: what agents need Two ways to connect AI agents to outside data: a router that offers many paid tools behind one key, and a data network that returns the record behind each value.
  14. 4 min read What should the source record behind an AI answer contain? Seven parts that make an AI answer checkable, from the source and record ID to attestation dates and unknowns, shown on seven real company lookups.
  15. 5 min read How AI agents get live data and tools, and how to choose Search, page extraction, specialist data APIs, generation models and MCP: how an AI agent reaches the outside world, with a worked example on real records.
  16. 4 min read How to check where an AI answer came from A five-step check for any AI answer, worked through on real public records, and what good provenance looks like when you need to rely on a fact.
  17. 4 min read What to ask before you connect an agent to a data gateway Eight questions for any agent data gateway, applied to IKAG in early access: provenance, failures, routing, cost, own keys, retention, terms.
  18. 3 min read What is an intelligent data network for AI agents? What IKAG, in early access, means by an intelligent data network for AI agents, and how it compares with single APIs, marketplaces and MCP servers.
  19. 3 min read What IKAG’s first capability does, and won’t do Seven offline requests to IKAG’s first capability, in early access: what it answers, what it leaves unknown, and why a shared name never joins two records.

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