Secular Labs
AI-native business transformation

We study how ultra-lean businesses scale — then help you become one.

Secular Labs advises founders and operators on restructuring around Autonomous Micro-Enterprise Architecture (AMEA): the same agent-orchestration and verification principles behind 2–10 person teams reaching outsized revenue per head. We apply it two ways — as strategic consulting for existing businesses, and as production AI systems for advertising technology.

Start a conversation See how we work
Intake Reasoning Retrieval Validation Delivery
3–100xrevenue-per-employee growth range we design engagements around, by company stage
5working papers formalizing the AMEA / AMEE / AMEG / AMEF framework
6stages in our production agent-deployment architecture
3AI-native plugins live in AdTech production now, 2 more shipping within weeks
What we believe

A business no longer needs to add headcount to add throughput — it needs the right architecture.

Think of it the way economists think about GDP per capita: a country's total output doesn't tell you much on its own — divide it by population, and you learn how well that output is actually shared. Revenue per employee works the same way for a company. A handful of well-known AI-native companies — Midjourney and Medvi among them — are widely cited industry examples of this pattern, generating revenue-per-employee figures many times higher than a similarly sized business run the traditional way, without a proportionally larger team. (They're referenced here as public industry data points, not as Secular Labs clients or case studies.)

AMEA — Autonomous Micro-Enterprise Architectures
The "how": a technical blueprint for orchestrating AI agents so a small team can run what used to require a much larger one.
AMEE — Autonomous Micro-Enterprise Economics
The "why it pays off": the economic reasoning showing this lowers coordination cost and turns open-ended risk into a fixed, predictable one.
AMEG — Autonomous Micro-Enterprise Governance
The "who's accountable": a verification and audit architecture that maps to regulatory frameworks as they emerge worldwide — the EU AI Act being the most developed example today — so governance is built into the system rather than added after the fact.
AMEF — Autonomous Micro-Enterprise Finance
The "how it gets priced": a framework for how investors and capital allocators should value and underwrite these firms, replacing metrics like burn multiple and revenue-per-employee with ones built for compute-and-verification-driven organizations.

A third paper applies the framework specifically to programmatic AdTech clearing: OpenRTB bid streams, IAB compliance, and verification at exchange scale. A fourth formalizes the governance layer, and a fifth formalizes how capital allocation and valuation work under this model. Together, they're the independent research program our founder has developed — published as working papers and submitted toward peer-reviewed venues (SSRN, IEEE, and NBER-affiliated conferences). Secular Labs exists to put that research to work: first as a diagnostic and advisory engagement for operating businesses, and second as applied engineering — we build and run these systems ourselves, not just advise on them.

Revenue per employee — illustrative example $150k Traditional operating model $900k+ AMEA-restructured operating model

Illustrative only — actual uplift depends on which functions move to orchestration and how much verification overhead they require.

Where we work

Three fronts, one underlying architecture

  • AMEA/AMEE growth & governance advisory

    Strategic consulting for operating businesses — traditional and AI-native alike — that want to restructure around agent orchestration. For established companies, that typically means 3–4x revenue growth over 24 months; for a startup or early-stage business building this way from the outset, the same architecture can support 50–100x, since there's no legacy headcount or process to unwind first. A verification layer is built in from day one either way. Our primary practice.

  • Applied AdTech AI

    Production plugins for programmatic advertising — invalid-traffic detection, conversational analytics, RTB intelligence, banner generation — shipped through our engineering practice and available at reviveadservermod.com. Our proof that the architecture works under real load.

  • AdContext Protocol (AdCP)

    We've worked on AdCP, an open standard for agent-to-agent advertising workflows — audience discovery, negotiation, and campaign activation conducted directly between advertiser and publisher agents. A concrete example of what agentic commerce looks like in production.

Who this is for
  • 01

    Startups aiming for aggressive growth

    Founders who want to scale revenue and operations significantly without matching headcount growth, and need a credible multi-agent architecture — not just another chatbot or automation layer.

  • 02

    Traditional / established businesses

    Operators looking to increase capacity and revenue by redesigning how work is coordinated, instead of adding layers of headcount and management.

  • 03

    AdTech and programmatic teams

    DSPs, SSPs, and OpenRTB/programmatic platforms exploring agentic bidding via AdCP, invalid-traffic detection, or conversational analytics on top of infrastructure they already run.

  • 04

    Researchers and academic collaborators

    Academics working on the economics or governance of multi-agent systems, organizational-boundary theory, or AI-native venture design — we're always glad to compare notes.

Meeting in Europe this autumn

Where to find us

DatesCityNote
Sep 21–27CologneDMEXCO runs Sep 23–24
Sep 28–Oct 3FrankfurtOpen for meetings
Oct 5–14BerlinOpen for meetings
Oct 26–30FrankfurtAI Week Frankfurt

If you're working on agentic advertising, AI governance, or the economics of automated businesses, we'd like to talk.

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