Generative AI
Infosys
Infosys built Topaz, its generative and agentic AI suite, and Topaz Fabric, a composable stack of…
Area
Generative AI, in enterprise use, means applications built on large language models: drafting, summarising, extracting and classifying. The distinction from agentic AI is that a generative application answers what it was asked, rather than deciding what to do next.
Generative AI
Infosys built Topaz, its generative and agentic AI suite, and Topaz Fabric, a composable stack of…
Generative AI
Cohere made a deliberate bet against the consumer chatbot race that defines OpenAI, Anthropic, and Google,…
Generative AI
Mistral built the only credible frontier-scale alternative to the American labs, and it built it around…
Generative AI
Amazon built the largest neutral distribution channel for third-party foundation models through Amazon Bedrock, rather than…
Generative AI
Every model on this list, and nearly every generative AI system built by any company anywhere,…
Generative AI
Meta took a different route to leadership than every other lab on this list: it gives…
Generative AI
Google occupies a position none of the other frontier labs can match: it researches the model,…
Generative AI
OpenAI holds the largest distribution in consumer and developer generative AI by a wide margin. ChatGPT…
Forward Deployed Engineering
Microsoft turned its 27% ownership stake in OpenAI and its existing enterprise footprint into the largest…
Generative AI
Explore the best generative AI consulting companies, spanning specialist AI delivery firms, strategy consultancies, and global…
Generative AI, in enterprise use, means applications built on large language models: drafting, summarising, extracting and classifying. The distinction from agentic AI is that a generative application answers what it was asked, rather than deciding what to do next.
Area reviewed 12 Sep 2026
What the work involves
The model is rarely the hard part. The work is retrieval over your own documents, output validation, human review paths and the accuracy measurement that tells you whether any of it helped. Firms that lead with prompt engineering as a discipline are describing the easiest 10% of the project.
Who buys it
Legal, claims, procurement and finance teams buy this first, because they hold large volumes of text that people currently read manually. The budget usually sits in the function rather than in IT, which speeds up the pilot and slows down the production deployment.
Firms in this area
See all 42 firms in this area
What to ask
Research notes
This is the largest and least differentiated area we cover. We track 42 firms and rank none of them overall, because the work is too task-specific for a single ordering to be useful. Instead we assess by use case: document extraction, drafting, classification and summarisation are effectively four different markets with different leaders.
| Use case | Firms with production references | Assessment status |
|---|---|---|
| Document extraction | 14 | Ranking published Q4 |
| Drafting and summarisation | 19 | In progress |
| Classification and routing | 11 | In progress |
| Conversational support | 9 | Not started |