How is this different from a traditional data room?

Every data room today — from a Dropbox folder to a purpose-built VDR like Datasite or Ansarada — is a store of static documents that go stale the moment you upload them. dealflow.fyi reads live from your Stripe, MongoDB, PostHog and ClickHouse — the same systems a buyer would verify against — and refreshes every document from that source on a single command.

Where do the numbers actually come from?

Directly from your production systems via read-only connections. Each sync writes a dated, immutable snapshot, and every figure in every document traces back to the exact file that produced it.

We use restricted, read-only keys and never write to your systems. Snapshots are immutable, access is confidential, and the full history is auditable — you can always see exactly what was pulled and when.

What is the Agent-Readiness report?

It scores how discoverable and usable your product is to AI agents — the fastest-growing class of buyer. As agents begin selecting and purchasing software autonomously, agent-readiness becomes a real driver of value, and the report makes it legible to an acquirer.

What kinds of businesses do you work with?

Software, API, and autonomously-run internet businesses, generally between $1M and $50M in enterprise value. If your revenue and usage live in systems we can read, we can build the room.

Do you replace my banker and lawyer?

No — we make them faster. We own the data and the documents so diligence moves quickly; your counsel handles the paper and your banker handles the relationship. Everyone works from one source of truth.

How does pricing work?

The Data Room product is a flat monthly fee you run yourself. Managed Sale is a success fee — from 2% of transaction value — where we run the process end to end on top of the same product. Studio is bespoke for funds and serial acquirers.

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Agent-readinessAugust 18, 2026 · 7 min read

Your next buyer is an AI agent. Is your company legible to one?

AI agents already research, shortlist, and increasingly buy software on their own. The companies legible to them get found, trusted, and valued higher. The rest go invisible.

For twenty years, being found meant ranking on a page of blue links so a human could click one. That era is ending. A fast-growing share of software is now discovered, evaluated, and — increasingly — purchased by AI agents acting on a buyer's behalf. The question that follows is uncomfortable and concrete: when an agent goes looking for what you sell, can it find you, understand you, and trust you enough to act?

This is not speculative

The shift is already measurable:

Gartner projects that 90% of B2B procurement will be managed by AI agents within three years, a volume north of $15 trillion.
Forrester expects roughly one in five B2B sellers to face agent-led quote negotiations by the end of 2026.
Agentic checkout is already shipping — Microsoft Copilot Checkout and Shopify's agentic storefronts went live in early 2026, and one payments network processed 120 million agent transactions in a single week.

Buyers increasingly do not browse. Their agents do the research, narrow the field, and hand over a short list — or complete the purchase outright.

What "agent-readiness" means

Agent-readiness is a simple test with four parts. Can an agent:

Find you — are you present and legible where models look, not buried behind a JavaScript wall or a login?
Parse you — is what you do stated in plain, structured language a machine can extract without guessing? Schema, clean entities, machine-readable docs like llms.txt, an agent capability card, an OpenAPI spec.
Verify you — can your key claims be checked against something, rather than taken on faith from marketing copy?
Act — is there a clear, unambiguous next step an agent can take on a buyer's behalf?

Most companies fail at step two and never learn why. They are invisible not because the product is weak, but because it is illegible to the reader that now matters.

Why this becomes a valuation input

Here is the part acquirers have started to price. A business that AI agents can discover and trust has a structurally cheaper, more durable path to demand than one that depends on winning a human's attention in a feed. That is lower customer-acquisition cost and a distribution moat that compounds as agent-mediated buying grows. An acquirer underwriting your future growth — which is what they are paying for — will pay more for a company that is already legible to the channel the whole market is moving toward.

Agent-readiness is becoming to the 2020s what SEO was to the 2010s: an invisible asset that quietly determines who gets found, and a real line item in what a company is worth.

AEO is the near-term expression of it

The immediate, testable version of agent-readiness is Answer Engine Optimization — getting cited inside the answers that ChatGPT, Perplexity, Claude, and Google's AI Overviews write. The practices that win are the same ones that make you legible to a buying agent: structure content around real questions, add schema, be genuinely verifiable, and earn authoritative mentions. (This very post is built that way — the shape is the argument.)

The takeaway

Your next buyer, or the analyst screening for them, is increasingly an AI agent.
Agent-readiness is a four-part test: find, parse, verify, act.
Legibility to agents lowers acquisition cost and compounds — which is why it is starting to move valuations.
The near-term move is AEO; the durable move is building a company a machine can trust.