Miksi

Miksi gives AI assistants the truth about your product so they recommend it to the right people

Upload your docs. We extract fit signals. Agents query your endpoint before routing users to a trial.

Get started for freeNo credit card required

ChatGPT is recommending your product right now. Probably to the wrong people.

AI agents are guessing

They work from scraped marketing copy, not structured fit data.

Wrong recommendations

Users who were never going to convert start trials and churn.

You pay for bad fits

High CAC for misqualified leads. Low conversion rates.

How it works

Three simple steps to machine-readable product truth

Upload your product docs

AI reads them and extracts fit signals: who it's for, who it's not, and where it breaks down.

Review the signals

Edit, add, or remove. You control what agents tell your prospects.

Publish your endpoint

Agents query it before routing users to a trial. Fewer bad fits. Better conversions.

Why it works

Built for the reality of AI-assisted decision making

Structured signals, not marketing copy

Agents get use cases, anti-use cases, constraints, and deal-breakers — the stuff that actually qualifies a user. Not your About page.

One endpoint, every agent

Standard HTTP. No SDK. ChatGPT, Claude, Perplexity, Gemini — any agent can query it without a special integration.

Upstream of your funnel

Miksi works before the user hits your site, while the AI is still deciding what to recommend. Fix the filter, not the funnel.

Your positioning docs already explain who you're for.

Let's make that machine-readable.

Get started for freeNo credit card required

Agent-readable product surface

Canonical endpoint: https://miksi.dev/v1/surface/miksi

MIKSI_SURFACE v1
product: Miksi
endpoint: https://miksi.dev/v1/surface/miksi
primary_use_cases:
- PLG SaaS founders and teams with free trials who want to improve lead intent before users enter the trial.
- Products where high-intent users convert better when constraints, failure modes, and non-fit are stated plainly upfront.
- Any individual or organization that wants to expose structured fit signals to AI agents for discovery filtering, including consultants, open-source maintainers, and creators.
anti_use_cases:
- Not for enterprise procurement or sales-led motion contexts.
- Not an SEO tool, review platform, lead gen service, chatbot, or ranking and comparison platform.
- Not for vendors seeking paid promotion, competitive positioning, or optimization for agent preference.
constraints:
- There is no chat interface or embeddable widget. The public-facing product is a standard HTTP API endpoint.
- Miksi intervenes before the funnel and cannot attribute downstream business metrics like revenue or retention.
- Discovery uses the A2A protocol. Queries are plain HTTP REST — no SDK required.
assumptions:
- AI agents increasingly mediate product discovery, and discovery is shifting toward agent-to-agent interactions.
- High-intent users are not discouraged by explicit tradeoffs — they convert better when constraints and non-fit are clear.
- Filtering intent earlier in the discovery flow results in higher-quality trials, though downstream outcomes depend on factors outside Miksi's control.
misunderstandings:
- Miksi improves lead intent before the funnel. It does not measure revenue, conversion, or retention — downstream outcomes are not attributable.
- The goal is not to increase traffic or signups; the goal is higher intent density among users who decide to try.
- Miksi optimizes for correct fit, not competitive advantage, visibility, or persuasion.
END_MIKSI_SURFACE