Civico
Research library

What leaders should know about AI, with the sources.

An open library that feeds every Civico programme and a weekly Insight. Every number links to a source we opened; every score is computed from the rows.

First entries arriving. This is the library's seed state: the taxonomy of technologies, workflows and industries is in place. We are collecting the first sourced entries for this view. Each one will link to the page it came from, and nothing here is a finding until it does.

Funding Map

Which AI startups are being funded: company, round, amount, date, investors, workflow, industry and source.

No rows yet →

AI Radar

23 technologies across models, agents, data, applications and infrastructure, scored for maturity and momentum at build time.

0 of 23 with evidence →

Workflow Map

36 workflows and what is being disrupted in each, and by whom.

0 of 36 with evidence →

Use cases

Named deployments, surveys, filings and case studies showing AI at work.

No rows yet →

Industry heatmap

Which industries AI and agents disrupt most, by function, with the evidence behind each cell.

0 of 14 with evidence →

Agentic tracker

What agents can reliably do now, from dated benchmark results with primary sources.

No results yet →

What we are researching next

Ten questions leaders keep asking us, and the evidence we are gathering to answer them.

  1. Where do AI pilots stall before they reach the P&L?Why so many pilots stall between demo and budget, and what the ones that cross have in common.
  2. Which functions are adopting agents first, and how deep?Which functions are putting agents into daily work first, and how far they have gone.
  3. How does AI capital spending compare with AI revenue?How much of today's AI market is paid for by customers rather than investors.
  4. What is shifting in workforce and skills?Which roles, tasks and skills change first, and what employers say they will pay for.
  5. How do AI rules differ by region?How rules on AI, data and procurement differ across Asia, the US and Europe.
  6. Where does Asian AI funding differ from the US and EU?Which workflows and industries attract capital in Asia, and who funds them.
  7. Which evals should leaders ask vendors for?A short list of tests and evidence a leadership team can ask for before funding a project.
  8. What do board-ready AI decisions look like in practice?Projects that were funded, parked or stopped, and the evidence that decided each.
  9. Which AI startups are replacing software seats with finished work?Whether AI-native products are priced and bought differently from software seats.
  10. How reliable are agents on long tasks?Where agents stay reliable on long tasks, and where they still break.

How it feeds the Insights

Each week one short editorial draws on these views and links back to the rows behind every claim. Read the Insights → · How we score →