Research vs Writing AI moats
Research AI has the wider moat: an average of 56 out of 100 against 37 for Writing AI, 19 points apart. They rank 21st and 29th of 29 AI markets. Research rates a narrow moat and Writing no moat. Research is stronger on hard to copy, switching costs, habit and retention and ecosystem. Research is less crowded, with a saturation of 14 against 65 for Writing. On FalcoScan's data Research is both better protected and less crowded.
Side by side
The two markets on FalcoScan's moat rating, crowding and threats. The better figure of each pair is in bold; for crowding, threats and the no-moat share, lower is better.
| Measure | Research | Writing | Better |
|---|---|---|---|
| Moat rating | Narrow moat | No moat | |
| Average moat | 56 of 100 | 37 of 100 | Research, by 19 points |
| Rank among AI markets | 21 of 29 | 29 of 29 | Research, by 8 places |
| Main moat | Hard to copy | None | |
| Products with a wide moat | 3% | 0% | Research, by 3 points |
| Products with no moat | 26% | 82% | Research, by 56 points |
| Saturation (crowding) | 14 | 65 | Research, by 51 points |
| Wrapper exposure | 1% | 65% | Research, by 64 points |
| Platform dependency | 23 | 47 | Research, by 24 points |
| Products rated | 142 | 321 |
Moat sources
Each source and threat on a 0 to 100 scale, averaged across each market and rated against all AI markets.
Research, filled · Writing, dashed
Where Research is stronger
- Hard to copy+39
- Switching costs+13
- Habit and retention+13
- Ecosystem+13
Where Writing is stronger
No moat source more than 5 points ahead of Research.
Widest moats in each market
The five products with the highest moat score in each market, shown as bands. Exact scores are on paid plans.
Widest moats in Research
- 01Lila SciencesAutonomous AI scientistWide moat
- 02NotCoAI-driven plant-based food formulationWide moat
- 03Open Alex Research APIFree open API for 250 million scholarly works with AI filteringWide moat
- 04InstaDeepDecision-making AI for the enterpriseWide moat
- 05Periodic LabsAI scientist for accelerated researchNarrow moat
Widest moats in Writing
- 01AcrolinxEnterprise content governance and AI writing alignmentNarrow moat
- 02Roam ResearchThe original networked thought tool for serious thinkers and writersNarrow moat
- 03Wordsmith by Automated InsightsNatural language generation that turns data into written narrativesNarrow moat
- 04LogseqOpen-source networked knowledge base with AI writingNarrow moat
- 05SciSpace AI ResearchAI co-pilot for reading scientific papersNarrow moat
More comparisons
Each market against its closest rivals by moat, and against the widest and narrowest markets. The figures are the two average moats.
Research against
Questions
Which has a wider moat, Research AI or Writing AI?
Research AI, with an average moat of 56 out of 100 across 142 rated products, against 37 across 321 in Writing AI. 3% of Research products have a wide moat, against 0% in Writing.
Is Research AI or Writing AI more crowded?
Research is less crowded, with a saturation of 14 against 65 for Writing. Saturation runs from 0 to 100 and measures how crowded a market is. On FalcoScan's data Research is both better protected and less crowded.
How do the moats of Research AI and Writing AI differ?
Research's main moat is hard to copy and Writing's is none. Research leads on hard to copy (+39), switching costs (+13), habit and retention (+13) and ecosystem (+13).
Is Research AI or Writing AI more exposed to wrappers?
Writing AI: 65% of its products could be rebuilt on a public model quickly, against 1% in Research AI.
Which Research and Writing AI products have the widest moats?
In Research: Lila Sciences, NotCo and Open Alex Research API. In Writing: Acrolinx, Roam Research and Wordsmith by Automated Insights. Exact moat scores for every product are on FalcoScan's paid plans.
Cite and share
Quote a figure, link to the comparison or take the data for every market.
FalcoScan, “Research vs Writing AI moats”, data updated 9 October 2026. https://falcoscan.com/moats/compare/research-vs-writing
@misc{falcoscan_moats_compare_research_vs_writing_2026,
author = {{FalcoScan}},
title = {Research vs Writing AI moats},
year = {2026},
month = oct,
howpublished = {\url{https://falcoscan.com/moats/compare/research-vs-writing}},
note = {Data updated 9 October 2026}
}<a href="https://falcoscan.com/moats/compare/research-vs-writing">Research vs Writing AI moats (FalcoScan)</a>
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