What 843 AI agencies actually sell
We mapped 843 AI agencies across India, the US and Europe: what they sell, where they are, which offers are crowded, which are thin, and what to check.
Chapters · 07
Between 17 and 22 September 2026 we built a workbook of every AI agency, consultancy and AI-native delivery firm we could find: 843 firms across India, the US, Europe and a long tail of other regions. We wanted to see the market the way a buyer does. Every count below was computed from that workbook; the method is at the end.
The short version: most of the market sells the same two things, automation and custom builds, which together account for 457 of the 843 firms. Only 31 sell audit, security or testing. And the work a team needs once something is in production, evaluation, monitoring and someone on the hook when it breaks, is the thinnest part of the map.
What we counted and how
Eight research passes (Americas and ANZ, India, Europe and the Middle East, design-led studios, consulting and advisory, Asian, vertical and voice agencies, AI-code cleanup, freelancers), directory sweeps (Clutch, GoodFirms, DesignRush, Sortlist, and the n8n, Make and Zapier directories), and 211 firms carried over from our earlier landscape note. Duplicates were merged on domain. Of the 843 sites, 819 loaded and 619 homepages were read on the research date.
Each firm has a region, one of 35 segments, a size band and a description of what it does. Kept separately, outside the 843: 90 firms that fix AI-generated code, 103 independent consultants, and a 40-row catalogue of every offer type we saw, each rated by how many credible sellers it has.
One caveat: size is known for only 274 of the 843. Most firms do not say how big they are, which matters later.
The regional shape
The regions sell different things. India’s 209 are build shops: 46 dev studios, 27 boutiques, 21 mid-sized IT firms, 29 automation agencies. The US mix is flatter: 21 vertical agencies, 21 automation agencies, 19 dev studios, 11 forward-deployed engineering firms and all 9 big-consultancy AI arms. Europe holds the incumbents: 31 IT majors and consultancies, 15 nearshore firms, 14 data engineering firms. The UK leans to advice: 6 of the 14 governance firms and 5 of the 11 training firms are British.
What firms sell
The 35 segments group into nine offer families. The grouping is ours; every firm lands in exactly one.
| Offer family | Firms | Segments inside |
|---|---|---|
| Automation and agents as a service | 246 | 142 SMB automation agencies, 70 vertical agencies, 26 voice-AI agencies, 4 productised services, 4 automation-and-coaching hybrids |
| Custom build | 211 | 123 dev studios, 27 Indian boutiques, 26 design-led studios, 15 nearshore firms, 11 engineering firms with an AI practice, 9 AI-native delivery firms |
| Embedded and enterprise delivery | 123 | 35 FDE firms, 31 IT majors based in Europe, 21 Indian mid-sized IT firms, 9 big-consultancy arms, 8 established Indian engineering firms, 7 platform-plus-services firms, 6 IT-major practices, 6 lab and hyperscaler arms |
| Advice and strategy | 117 | 51 AI consultancies, 19 research and advisory, 17 strategy consultancies, 12 industry consultancies, 12 MSPs, 6 fractional-leadership firms |
| Data engineering | 62 | 50 data and AI engineering firms, 12 analytics consultancies |
| Audit, security and QA | 31 | 14 governance and compliance, 10 security and red-teaming, 7 QA and testing |
| Platforms and tooling | 26 | 15 AI-native startups, 11 developer-productivity and AI-impact platforms |
| Training and community | 18 | 11 training firms, 7 coaching communities |
| Other | 9 | Uncategorised |
Automation-as-a-service and custom build account for 457 of the 843; audit, security and QA are 31. That ratio is the most useful fact in the workbook. Almost everyone will build the thing. Very few will tell you whether the thing is safe, correct or still working a month later.
What is crowded and what is thin
The catalogue rates each of the 40 offers by how many credible sellers we found: 22 crowded, 15 moderate, 3 thin.
Crowded:
- Custom builds (agents, RAG systems, voice agents, internal tools, integrations) are the default offer of nearly every automation agency. The catalogue’s note is that capability is much the same everywhere; firms differ by vertical depth or proof.
- Discovery and readiness audits take the least capital to start, so almost every new operator leads with one.
- Staff augmentation is the default Indian services business, with hundreds of Indian shops selling the same thing.
- AI support agents that resolve tickets are sold by nine platforms, bundled into the inbox the buyer already owns.
- Data plumbing for AI (pipelines, warehouses, vector databases) is offered by every data consultancy and is the easiest thing on the list to buy.
Thin:
- Evaluation harnesses, benchmarking and observability. Dozens of funded tool vendors, very few independents doing the implementation, because it takes real ML judgement.
- Data-quality and AI-data-readiness audits. Crowded as software, thin as a service a person delivers.
- Managed agents: monitoring, evals and a support SLA for AI systems already in production. Half a dozen vendors sell the dashboard; the human side, someone who answers when the agent breaks at 2am, is thin.
Codebase audit sits next to them, rated moderate: the automated side is crowded and well funded, and the human review is where the catalogue sees the gap. The cleanup list shows that gap starting to fill: 90 firms now sell cleanup of AI-generated code, 48 of them as a service line inside an existing dev agency and 13 as human audit specialists.
The firm counts say the same thing. 457 firms build. 31 audit, secure or test. 11 are platforms in the developer-productivity and AI-impact segment, measuring what AI is doing to engineering teams. Meanwhile the landscape’s Reddit sweep found an r/ExperiencedDevs thread titled “Getting more calls to fix ai generated codebases than actual new builds lately” at 405 upvotes.
What to check before hiring anyone
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Ask who will be on the work. Size is unknown for 569 of the 843, and a website rarely tells you whether you are talking to a two-person studio or a firm of 7,000. Ask how experienced the engineers are, who checks their code before it merges, and whether any of it is subcontracted.
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Ask what happens after the build. The market is crowded with builds and thin on evaluation, monitoring and support for systems already in production. Get a written answer on who maintains the thing, how a failure is detected and who answers when it breaks, before you sign for the thing.
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Ask how they will know it works. An agent or a RAG system without an evaluation harness is a demo. Few firms sell evaluation as a service, so ask to see the test set, the metrics and the regression checks for the system you are buying, and ask what happens when a model version changes underneath it.
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If you already have AI-generated code, get it read before you scale it. 457 firms will happily build on top of it; 31 sell audit, security or testing, plus the 90 cleanup firms outside the main list. A careful read finds the auth check missing on one route, the key committed to the repository and the same logic copied into several places. Each is easier to fix before the next feature lands on top of it.
What we do
Dravin AI is an AI software company. We build AI systems and software. Coding agents draft in parallel, each in its own isolated environment, automated checks run on every pull request, and an engineer approves each change before it merges. We also audit code and clean up AI-built apps.
What we build runs from agents, voice AI, fine-tuned models, classical ML and forecasting systems to web, mobile and desktop apps, and we deploy and run them in the cloud.
We also work in the thin part of this map: evaluation harnesses, and AI-generated codebases made safe enough for a real team to own. An engagement starts with a call. If any of the above describes where you are, book one and bring the repository.
Method
Every count comes from our research workbook, built between 17 and 22 September 2026 and counted on 22 September. The workbook itself is not published; these are the counting rules.
- 843: every firm on the main list; 211 of them came from our earlier landscape note.
- Regions: the region each firm is tagged with, exact match. The 82 is Global 33, Other 24, Unknown 23, Multi-country or remote 2. Europe is the tag as found; it holds some UK-based firms.
- Segments and families: each firm’s segment, exact match, filtered by region where one is named. The nine families are our grouping of the 35 segment values; the table is the mapping and it sums to 843. The 11 platforms are the segment “Dev-productivity / AI-impact platform”.
- Size: each firm’s size band: Solo 17, Micro 60, Small 97, Mid 76, Large 24, Unknown 569; 274 known.
- 819 and 619: sites that passed a link check, and homepages read on the research date.
- 90, 48 and 13: the firms on the cleanup list; those whose segment is a dev agency with a cleanup service line; those whose segment is a human audit of AI-generated code.
- 103 consultants: the firms on the list of independent consultants and freelancers.
- 40 offers; 22, 15, 3: the offer catalogue’s 40 entries, each rated crowded, moderate or thin by how many credible sellers we found. The crowded and thin notes paraphrase the catalogue’s notes on custom builds, discovery and readiness audits, staff augmentation, support agents, data plumbing, evaluation, data-quality audits, managed agents and codebase audit.
- The r/ExperiencedDevs thread (405 upvotes): from the Reddit sweep in our AI-agency landscape note.