Foaster

The AI-native McKinsey

2.2Score#627 of 999 agents#4 of 6 in Business analyst

Why it ranks #627

Foaster, an AI business analyst from YC Sp26, ranks #627 of 999 AI agents and #4 of 6 in Business analyst, with a score of 2.2 of 10. Data as of 3 Oct 2026.

The score adds four parts, each 0 to 10, by weight. Every point comes from public evidence. How scoring works ·

Proof 0 × 30% 0.0
Scale 1 × 30% 0.3
Momentum 4 × 25% 1.0
Autonomy 6 × 15% 0.9
= 2.2

Proof
Do customers use it? 30% of the score
0
No public claims of customers or revenue yet.
Not found: revenue or growth (+4), named customers (+3), a customer result (+2), a customer count (+2), work done at scale (+2)
Scale
Is there a real company behind it? 30% of the score
1
2 people.
- +1
  2 people on its YC page2 people
Not found: funding round in its news (+3)
Momentum
Is it shipping and growing now? 25% of the score
4
Shows a recent launch and a new batch.
- +3
  Launched in the last 6 monthsFoaster - AI agents that drive your AI transformationLaunch YC post · 5 May 2026
- +1
  New: YC Spring 2026
Not found: open roles on YC (+2), new traction claim in the last 6 months (+2), funding news in the last year (+2)
Autonomy
How much of the job does it do on its own? 15% of the score
6
Supervised agent: takes actions in other systems; a person approves key steps.
- +6
  Level 2 of 4: Supervised agentTakes actions in other systems; a person approves key steps.
What the model read
- Acts in other systems: 34% likely
- Finishes whole tasks: 14% likely
- Calls itself an agent: 98% likely
- Level 1 from the model's reading of its pages; the evidence review found, with quotes, that its AI acts in the work, so the level is 2
- An AI-native service: it sells the finished work, so it counts as an agent at any level
Level 2: Takes actions in other systems; a person approves key steps.

About Foaster

Foaster is building the AI-native McKinsey, starting with AI transformation.

We deploy AI agents that interview a company's employees at scale, map how work actually gets done, identify bottlenecks and AI opportunities, and draft a transformation roadmap in just 2 weeks. Expert consultants review the final outputs, add judgment where it matters, and feed their corrections back into the system.

We believe current AI models already have the capabilities required to automate most of the work consultants do. But traditional consulting firms use them to improve the old model: helping consultants work faster.

Foaster is instead rebuilding a new model from scratch, where agents do the work that needs scale and humans review the final outputs, bring expertise, and improve the system overtime.

We are starting with AI transformation, then progressively expanding to more and more consulting projects using the same approach. Every mission creates structured knowledge from interviews, workflow maps, recommendations, and expert corrections, so the system gets better with every client engagement.

The $500B consulting market will eventually be run by our AI agents and a small number of expert humans.