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FORKOFF
For foundation-model labs · By application · Selective on ICP

LLM marketing that takes you fromlab to product.

FORKOFF for Foundation Models is an LLM marketing engagement for foundation-model labs covering developer evangelism, research-to- revenue narrative, lab-to-product translation, and AISO citation across ChatGPT, Perplexity, Gemini, and Claude. One spine readable by researcher, developer, and procurement. Qualified-view proof every Friday.

Talk to FORKOFF
See the system
Diagnostic floor (by application) · routes to AEO + Perplexity SEO + DevRel + marketing foundation + podcastBy application · 3 lab engagements per quarterSeries B · Series C · Late-stage · Public
4×API trial-to-paid lift inside 90 days on a Series-C lab install
21Days to first research-to-revenue narrative arc in market
by applicationEngagement band per quarter (lab-tier diagnostic to embedded)
3Lab engagements per quarter (selective on ICP)
The short answer

What is LLM marketing, and how do you market a foundation-model lab?

LLM marketing runs the distribution a foundation-model lab has no in-house engine for: answer-engine and Perplexity optimization so your models are cited inside AI answers, developer evangelism, a research-to-revenue narrative, a marketing foundation, and podcast distribution aimed at adoption and the next round. FORKOFF is an outcome-priced marketing partner for foundation-model labs. It seeds each release into a distribution network that has processed 5B+ qualified views, syndicates research and founder proof across creators and channels in parallel, and reports on qualified views produced rather than retainer hours.

▸ Outcome-priced on qualified views, not retainer hours. Routes across AEO, Perplexity SEO, marketing foundation, and podcast by stage. Updated 2026-07-25.

Lab archetypes FORKOFF runs distribution for
Frontier labsOpen-weights labsInference platformsFine-tune providersEmbeddings APIsEval infrastructureModel gatewayMultimodal labsSafety researchAlignment researchSpeech modelsVision modelsFrontier labsOpen-weights labsInference platformsFine-tune providersEmbeddings APIsEval infrastructureModel gatewayMultimodal labsSafety researchAlignment researchSpeech modelsVision models
Series B → PublicFrontier + open-weightsResearcher cadence lockedAudit ledger per dollar

As Featured In

Full press shelf
By the numbers

The AI recall shift, in numbers.

Foundation-model labs win or lose discovery inside AI answer engines now. Here is the sourced picture behind the AEO and GEO work in this engagement.

  • Gartner projected that traditional search volume will fall 25% by 2026 as buyers move to AI chatbots and answer engines. (Gartner, 2024)

  • A page cited inside a Google AI Overview earns 120% more organic clicks per impression than an uncited page on the same result. (Seer Interactive, 2026)

  • Only 38% of AI Overview citations now come from a Google top-10 page, down from 76%, so ranking first no longer earns the citation. (Ahrefs, 2026)

  • Adding cited statistics to a page lifts its visibility in generative-engine answers by 41%, authoritative-source citations by 115%, and expert quotations by 28%. (Princeton GEO study, 2024)

  • Brands in the top web-mention quartile earn 10x more AI Overview mentions than the next quartile. (Ahrefs, 2025)

  • Google users click a traditional result only 8% of the time when an AI summary appears, versus 15% of the time without one. (Pew Research, 2025)

  • FORKOFF has processed more than 5 billion qualified views across its clipping network, the proof base behind the qualified-view reporting on this engagement. (FORKOFF, 2026)

Pre-engagement diagnostic

Why most foundation-model
lab GTM engagements stall.

Five patterns we see when a foundation-model lab shops for marketing help and the engagement reads as theatre inside the first quarter. Each row is the FORKOFF fix. Read it before you book the discovery call.

fk_audit · foundation_model_lab_reject_log.csv
  • Row 01
    Reject reasonThe lab is famous in research, invisible in shortlist
    Audit detail

    Papers cited five thousand times, the team speaks at NeurIPS and ICML, weights downloaded twice a week on HuggingFace. Yet when an enterprise buyer asks ChatGPT or Perplexity for a model shortlist, the lab is missing from the answer. Research recall did not translate into commercial recall.

    FORKOFF fix

    AISO citation work + answer-first capability docs + per-LLM shortlist tracking land the lab inside buyer-LLM responses on category queries inside 60 days. Research credibility compounds into commercial pipeline once the answer surface knows the model exists.

  • Row 02
    Reject reasonDevelopers love the model, finance can't sell it
    Audit detail

    The Discord is loud. The eval scores look great. Developers ship side projects on the API every weekend. Yet the GTM team cannot articulate the buyer story to a CIO, a VP of AI, or a procurement committee. The deal stalls between a curious developer and a sceptical signing authority.

    FORKOFF fix

    Lab-to-product evangelism translates eval rigor into procurement-grade narrative. Capability claim, benchmark proof, deployment path, safety story, pricing logic. One spine readable by both the engineering champion and the budget holder.

  • Row 03
    Reject reasonOpen-weights release goes viral then goes silent
    Audit detail

    Weights ship on HuggingFace. Twitter explodes for 48 hours. Fine-tunes appear in seven languages by week two. Then commercial signal flatlines. Hosting partners do not call. Enterprise design partners do not appear. The viral moment becomes a vanity peak instead of a pipeline trigger.

    FORKOFF fix

    14-day lab launch cadence + developer evangelism handoff + research-narrative arc convert the release spike into eight weeks of compounding commercial signal. Fine-tune adoption becomes hosted-API conversion. Open release becomes inbound demand for the closed-source enterprise tier.

  • Row 04
    Reject reasonResearch papers ≠ buyer-readable capability docs
    Audit detail

    The arXiv preprint is brilliant. The model card is dense. The system card runs to forty pages. Procurement reads none of it. Enterprise security reviews demand a one-page capability claim, an eval-to-deployment path, and a safety + privacy posture summary. The lab ships a paper, the buyer needs a brief.

    FORKOFF fix

    Research-to-revenue translation layer ships a buyer-readable spine alongside every paper. Capability claim, eval anchors, deployment recipe, safety posture, latency and cost band. Same rigor, procurement-readable. Schema-marked for AISO citation surface.

  • Row 05
    Reject reasonAPI trials activate and never convert
    Audit detail

    Developer activates the API key in two minutes. First few thousand tokens flow. Then the trial dies. No outbound from the lab, no usage-based onboarding, no sales-assist nudge at the procurement threshold. Conversion to a paid tier or hosted enterprise contract drops below industry floor.

    FORKOFF fix

    Developer-evangelism funnel + usage-trigger narrative + sales-assisted enterprise handoff plug into the API trial. Trial-to-paid lift tracked weekly on the audit ledger. The funnel respects developer trust (no spam) while opening the procurement door at the right usage moment.

5 / 5 patterns auditedSource: FORKOFF lab engagement bankPre-application diagnostic
The wedge

Researchers know the paper.
Buyers can't find the model.

DevRel agencies sell developer-only motion. PR firms sell press placements. Both leave the procurement layer empty and the AISO surface untouched. FORKOFF ships research-to-revenue translation, developer evangelism, and buyer-LLM citation across ChatGPT and Gemini. One spine, three audiences, one weekly receipt. The shortlist surface knows the model exists, and the procurement committee can read the capability brief in two minutes.

21Days to research-to-revenue spine
4Buyer LLMs tracked weekly
3Lab engagements per quarter (selective ICP)
Read the AEO wedge for labs
LIVEAudit ledger · lab engagement bench

Three numbers that decideif a lab engagement compounds.

0 days
Research-to-revenue spine signed by lab leadership
From scope-signed to capability docs locked. Standard across every 30/60/90 plan.
Per-LLM citation share across ChatGPT, Perplexity, Gemini, and Claude. Reported weekly.
First measurable AISO citation lift
0 days
Diagnostic floor: by application. Standard embedded retainer by application/mo. Routes to AEO, Perplexity SEO, DevRel, marketing foundation, podcast.
Lab engagement band
0/qtr
Application-only · selective on ICPSeries B · Series C · Late-stage · PublicQualified-view proof, audited every FridayScale-up or scale-down call at quarter end
What plugs into the lab engagement

Four phases. Twenty
deliverables behind the seat.

PHASE 01[WEEK 1-3]
01
Research narrative

Capability spine locked, buyer-readable docs shipped.

Deliverables (5)

  • ▸Capability claim signed by lab leadership
  • ▸Eval anchors selected (MMLU, HELM, custom)
  • ▸Research-to-revenue translation layer
  • ▸Buyer-readable capability docs (one-page)
  • ▸AISO baseline across 4 buyer LLMs
PHASE 02[WEEK 3-6]
02
Developer evangelism

Long-form developer content shipping in lab orbit.

Deliverables (5)

  • ▸Cookbook recipe series live
  • ▸HuggingFace model-card upgrade
  • ▸GitHub README depth pass
  • ▸AI Engineer + NeurIPS talk slot
  • ▸Developer Discord cadence locked
PHASE 03[WEEK 6-10]
03
Enterprise pipeline

Procurement-grade collateral + sourced inbound.

Deliverables (5)

  • ▸CIO-grade capability brief
  • ▸Security + safety posture document
  • ▸Design-partner case-study series
  • ▸LinkedIn institutional cuts shipping
  • ▸Analyst briefings booked (Gartner, IDC, RedMonk)
PHASE 04[WEEK 10-13]
04
Answer engine

Per-LLM citation share + trial-to-paid lift.

Deliverables (5)

  • ▸Schema graph + llms.txt published
  • ▸Per-LLM citation tracker live
  • ▸Trial-to-paid funnel instrumented
  • ▸Weekly audit-ledger receipt
  • ▸Quarterly scale-up or scale-down call
What counts on the lab ledger

What countson the weekly receipt.

A foundation-model lab engagement is only working when four signals hold every week. AISO citation logged on a model-shortlist query, developer recall lift inside the lab orbit, enterprise pipeline traceable to the research-to-revenue spine, and a compounding asset library that pays forward. Paper citation count without trial-to-paid lift or AISO citation share does not count. The audit ledger writes the four signals down on Friday with the operator signature.

Active check · AISO CITATION
1 / 4Signals the weekly report checks every Friday. AISO citation, developer recall, enterprise trace, compound asset.

01 AISO CITATION

Buyer-LLM citation logged on a model-shortlist query inside 60 days.

01

AISO CITATION

ChatGPT, Perplexity, Gemini, and Claude shortlist responses on category queries (best LLM for X, model for Y task, open-weights model for Z) name the lab and the specific model variant. Tracked per-LLM, per-query, per-week on the audit ledger. Citation share is the leading indicator of API trial volume before the signups land.

fk_audit · qv_check_01

rule · Buyer-LLM citation logged on a model-shortlist query inside 60 days.

02

DEVELOPER RECALL

API trial activations traceable to a specific cookbook recipe, HuggingFace model card upgrade, GitHub README arc, or AI Engineer talk slot. Plus mention tracking inside r/LocalLLaMA, r/MachineLearning, AI Engineer Discord, and the lab's own Discord channels. Developer recall is the precondition for everything downstream.

fk_audit · qv_check_02

rule · Trial signups attributable to operator-owned developer arcs.

03

ENTERPRISE TRACE

Design-partner conversations, hosted-API enterprise contracts, fine-tune custom-model deals, analyst briefing follow-ups. All traceable to a specific arc, asset, or AISO citation, not last-touch noise. Reported every Friday with the operator signature on the audit ledger.

fk_audit · qv_check_03

rule · Sourced procurement pipeline traceable to the research-to-revenue spine.

04

COMPOUND ASSET

Every research-to-revenue brief shipped this quarter remains a discoverable receipt next quarter. AISO citations carry over. Capability docs recompile into vertical arcs and round-readiness collateral. The library is yours to keep when the engagement ends.

fk_audit · qv_check_04

rule · Owned capability docs + AISO citations + research arcs that pay forward.

Counts on the proof
  • ›Perplexity model-shortlist response cites the lab's flagship variant
  • ›API trial activation attributed to a specific cookbook recipe
  • ›Hosted-API enterprise contract traceable to the capability brief
  • ›Analyst briefing converts to a Gartner research note mention
  • ›Design-partner conversation opened on a research-to-revenue arc
Doesn't count
  • ·HuggingFace download spike with no developer-evangelism handoff
  • ·Tier-one press placement with no AISO citation lift
  • ·Conference booth with no procurement-grade collateral on the table
  • ·Generic thought-leadership op-ed published with no capability claim
  • ·Press release announcing partnership with no buyer-readable spine
Outcomes the lab engagement unlocks

Citation, conversion,
and a real scale call.

Three lab campaigns across frontier dense, multimodal, and open-weights lanes. FORKOFF operators who owned the spine, scoped the research-to-revenue layer, and reported a weekly proof the lab leadership could read in two minutes. Read the longer write-ups inside our case-study hub.

4×

API trial-to-paid lift inside 90 days on a Series-C foundation lab. Replaced a high-touch monthly press retainer with embedded FORKOFF execution.

8 wk

Open-weights release converted into recurring commercial signal on a multimodal lab. Launch + 14-day evangelism cadence + analyst handoff turned the spike into eight weeks of hosted-API inbound.

60

Days from kickoff to first AISO citation on a frontier-lab engagement.

OWNED

You keep capability docs, eval anchors, cookbook, model cards, citation tracker.

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operator proof

What operators say after the first quarter.

“
The qualification ledger changed how we report to the board. Real attention, verified weekly, not dashboard vanity.
G

Growth lead

Series A, 2026, AI infrastructure startup

Brand
We went from guessing pipeline attribution to seeing it in a weekly audit ledger. Finance signed off on the next quarter before the first one ended.
M

Marketing director

Mid-market, 2026, B2B SaaS platform

Brand
FORKOFF ran our conference activation across three cities in one quarter. Side events, content capture, post-event distribution. One operator, one ledger.
H

Head of events

Three cities, one quarter, DevTools company

Partner
Geo-routing pulled the campaign out of single-market mode. India and Southeast Asia carried the qualified attention count. The unit cost dropped by two thirds.
C

Campaigns lead

India + SEA launch, Q1 2026, Consumer tech brand

Brand
99.71%Sustained legitimacy rate
3.4xRetained attention vs prior agency
250+Qualified introductions
4.2MQualified views in 14 days
Featured engagements
Voices from the field

What operators say about outcome-priced marketing.

Quotes from real buyer-side teams across AI, SaaS, Web3, and DevTools verticals.

Outcome-priced changed the conversation with our board. We pay for verified pipeline, not activity reports. The audit ledger is what our CFO actually reads.

Founder and CEO

AI startup, Series A

Same budget, 3.4x more retained attention. The unit of account matters. Qualified views are the only metric we report now.

VP marketing

B2B SaaS, mid-market

FORKOFF ran our developer conference activation end to end. Side events, podcast capture, post-event clip waterfall. One operator replaced three vendors.

Growth lead

DevTools, developer conference activation

The founder funnel compounded faster than any paid channel we tested. 30 minutes a day of founder voice, 50 named accounts, weekly warm intros. Built once, runs indefinitely.

Product marketing lead

Web3 protocol

Comparison

FORKOFF lab engagement vs the alternatives.

Four routes to foundation-model lab GTM durability. Match the engagement to the lab's stage, the model release cadence, and the procurement readiness target before picking. DevRel agencies, research PR firms, and DIY in-house GTM all lose on cross-audience fluency, AISO citation, and audit-proof transparency.

← scroll horizontally to see more →

FeatureFORKOFF lab engagementEmbedded · outcome-priced · research narrative + developer evangelism + AISO citationDevRel agencyHeadcount-priced · developer-only motion · no procurement layerResearch PR firmPress-release default · journalist relationships · no developer or AEO surfaceIn-house lab GTMFull headcount · 9-month assembly · researcher-led writing
Audience fluencySpeaks researcher, developer, and procurement on the same spine. Translates eval rigor into buyer-readable capability docsSpeaks developer fluently. Procurement and analyst layers handed off to clientSpeaks press fluently. Developer Discord and procurement language outsourced or skippedResearcher-led writing reads to peers, not to enterprise buyers. Hiring a translator takes 6-9 months
Pipeline driverDeveloper evangelism + AISO citation + research-to-revenue arc + procurement-grade collateralHackathons, conference booths, sample notebooks, Discord cadencePress hits, launch coverage, analyst quotes, op-edsWhatever the next senior hire prefers
Buyer trust sourceLab research credibility + eval anchors + per-LLM citation share + named design partnersDeveloper Discord activity + GitHub stars + sample app galleryTier-one outlet placements, analyst quotes, founder profile piecesVariance per researcher seniority. Roadmap re-litigated on every senior departure
Channel mixCookbook + HuggingFace + GitHub + AI Engineer + LinkedIn institutional + AISO citation + analyst briefingsGitHub + Discord + sample apps + DevRel conference circuitTier-one press + analyst quote sheets + founder bylines + thought-leadership op-edsWhatever the new VP of GTM prefers
Engagement modelEmbedded retainer, outcome-priced on trial-to-paid lift + AISO citation share + sourced procurement pipelineHourly retainer, output-priced on event count and impression reachMonthly retainer, output-priced on press placements and quote countSalary + equity + benefits + ramp + tenure variance per researcher
Speed to first assetResearch-to-revenue spine signed by day 21, first developer arc shipping by day 30Week 6 first cookbook entry, week 10 first conference boothWeek 4 first press hit, then quarterly cadenceRoughly 120-180 days, gated on hiring closing
Reporting surfaceWeekly audit-ledger receipt: trial-to-paid lift, sourced procurement, per-LLM citation share, design-partner pipelineMonthly recap. GitHub stars, Discord growth, conference attendanceQuarterly press clipping book. Reach estimates, quote countQuarterly board deck. Vanity metrics during ramp
Foundation-model lab engagement plans

Three routesfor foundation-model labs.

DevRel, foundation, or founder seat. Match the engagement to the lab stage and release cadence. By application, capped at 3 lab engagements per quarter.

01

DevRel

Cookbook plus HuggingFace plus AI Engineer cadence

by application/qtr
  • Cookbook recipe series
  • HuggingFace model-card upgrade
  • GitHub depth pass
  • AI Engineer talk slot
  • Discord cadence
Apply for DevRel
Most picked
02

Marketing Foundation

Capability spine plus AISO citation plus weekly receipt

by application/qtr
  • Capability claim doc
  • Eval anchor pack
  • AISO citation tracker
  • Schema graph published
  • Audit ledger weekly
Apply for Foundation
03

Founder Funnel

Lab founder authority plus research-to-revenue arc

by application/qtr
  • Founder long-form arc
  • LinkedIn institutional cuts
  • AI Engineer keynote prep
  • 30/60/90 cadence
  • Friday receipt
Apply for Founder Funnel

Note ·Diagnostic floor (by application) applies to the first cycle. Engagements scope-locked, not retainer guesswork.

Lab engagement fit diagnostic

Strong fit when 4+ are true.
Skip when any disqualifier fires.

Who you are
  • ›Shipping a foundation model (frontier dense, mixture-of-experts, multimodal, embeddings, speech, vision, fine-tune host, inference platform)
  • ›Stage Series B through public or late-stage growth (institutional capital, named research credibility, paying enterprise tier or hosted API revenue)
  • ›Lab leadership willing to commit research staff to a translation layer (2-4 hours per week with a senior researcher)
  • ›Real model running in production with eval anchors, design partners, or hosted-API revenue baseline
  • ›Commercial milestone in the next 90 days (model release, enterprise tier launch, partnership, NeurIPS talk, fundraise, IPO window)
  • ›Cares about AISO citation share, developer recall, trial-to-paid lift, and analyst presence, not just paper citation count
What FORKOFF delivers
  • ›Embedded operator who owns the research-to-revenue spine and runs weekly cadence with both research and GTM leadership
  • ›Capability docs + cookbook + AISO citation work + analyst handoff plugged in behind the seat
  • ›30/60/90 plan signed in week one with the per-LLM citation baseline captured
  • ›Cookbook recipes + HuggingFace upgrades + GitHub depth + AI Engineer talk slots + LinkedIn institutional cuts
  • ›Weekly audit-ledger receipt against trial-to-paid lift, sourced procurement, AISO citation share, and design-partner pipeline
  • ›Routes to /services/answer-engine-optimization, /services/perplexity-seo, /services/devrel, /services/marketing-foundation, /services/podcast based on the lab's stage and release cadence
Not the right fit
  • ×Pure academic research labs with no path to commercial milestone in 12 months
  • ×Application-layer AI startups (LLM apps, agentic apps, RAG tooling). Those route to /for/ai-startups
  • ×Labs unwilling to commit researcher time to the buyer-readable translation layer
  • ×Pure paid acquisition mandates with no developer evangelism or research narrative work
  • ×Operators who treat lab GTM as press-clipping engine, not citation share + trial-to-paid compounding
Apply for the lab engagement

Diagnostic floor (by application) · routes to AEO, Perplexity SEO, DevRel, marketing foundation, podcast

FORKOFF runs the foundation-model lab engagement as an embedded retainer with the FORKOFF execution stack plugged in behind it. By application, capped at 3 lab engagements per quarter, selective on ICP. Diagnostic floor (by application): (4-week capability spine + AISO baseline + research-to-revenue brief). Standard embedded retainer monthly retainer, by application. Frontier-lab multi-model coverage scopes per quarter, by application.

  1. 01Sandbox
  2. 02Engagement
  3. 03Compound
By application
Apply for the lab engagement
Markets we run this in

Lab engagements anchor on research clusters and procurement bridges. We seat the developer evangelism inside San Francisco and route enterprise + analyst surface through London GTM for the regulated buyer cohort. How buyers surface models in AI answers is covered in our guide on how AI Overviews rank brands.

Related lanes

Sister ICPsand routing services.

01 / 03Open

AI Startups

Sister ICP. Application-layer AI builder axis.

02 / 03Open

Dev Tools

Adjacent ICP. Developer-tool company axis.

03 / 03Open

DevRel service

Developer evangelism layer for lab APIs.

Frequently asked questions

How is FORKOFF different from a DevRel agency or a research PR firm for foundation-model labs?

A DevRel agency speaks developer fluently and stops there. Procurement, analyst, and AISO surfaces are out of scope. A research PR firm chases press placements and analyst quotes, with no developer Discord or buyer-LLM citation work. FORKOFF runs the full lab spine: capability claim translation, developer evangelism, enterprise pipeline collateral, and AISO citation across ChatGPT, Perplexity, Gemini, and Claude. One operator, one weekly receipt, three audiences (researcher, developer, procurement).

What does the foundation-model lab engagement actually cost?

Lab-tier engagements run by application per quarter depending on scope. Diagnostic floor (by application): (4-week capability spine + AISO baseline + research-to-revenue brief). Standard embedded retainer lands monthly retainer, by application. Frontier-lab engagements with multi-model coverage and analyst handoff scope per quarter, by application. All by application, capped at three lab engagements per quarter, scaleable up or down at quarter end. No clipping-style $0.003 CPQV pricing. Labs anchor on outcome bands.

Do you work with open-weights labs that have no commercial product yet?

Selectively. The bar is shipping signal (active weights releases on HuggingFace, growing fine-tune ecosystem, real eval anchors) and a clear path to commercial milestone in the next 12 months: hosted-API tier launch, enterprise design partnership, fine-tune custom-model contracts, or institutional capital window. The wedge is converting the open release spike into hosted-API inbound via the 14-day evangelism cadence plus analyst handoff. We are not the right fit for pure-research labs without a commercial axis.

Can you cover both developer evangelism and enterprise procurement on the same engagement?

Yes. That is the point of the lab spine. Developer evangelism on GitHub, HuggingFace, AI Engineer, and the lab Discord drives API trial signups and eval-rigor recall. Enterprise procurement collateral on LinkedIn, analyst briefings, and capability briefs converts those signals into hosted-API contracts and design-partner pipeline. Same research spine, different cuts, different cadence. The translation layer is the work that DevRel agencies skip and PR firms cannot write.

What does outcome pricing look like for a frontier or open-weights lab?

We anchor on API trial-to-paid lift, sourced procurement pipeline, AISO citation share across ChatGPT, Perplexity, Gemini, and Claude, design-partner conversion, and analyst briefing follow-through. Per-impression and CPM models do not apply. Frontier labs typically anchor on AISO citation share plus enterprise pipeline value reported on a weekly audit-ledger receipt. Open-weights labs anchor on hosted-API trial-to-paid plus fine-tune ecosystem signal.

How does AISO citation work for a foundation-model lab specifically?

Buyers ask ChatGPT, Perplexity, Gemini, and Claude for model shortlists every day: best LLM for code generation, fastest open-weights model under 70B, model with the strongest tool-use trace, lowest-cost embeddings provider. AISO citation work targets these category queries directly. We publish capability docs in answer-first structure, instrument schema graph, ship llms.txt, and track per-LLM citation share on the audit ledger. The lab lands inside the shortlist response on category queries inside 60 days.

How fast does the lab engagement go live?

Application call, scope locked inside seven business days, engagement starts week two. Research-to-revenue spine signed by day 21. First developer arc shipping by day 30. AISO baseline captured by day 14. First measurable citation lift typically by day 60. Quarterly scale call on day 90. Round-readiness or IPO-window narrative loaded by day 75 if a commercial milestone is inside the quarter.

How do you coordinate with the lab's existing research, DevRel, and PR teams?

FORKOFF embeds as the spine that connects research output, developer evangelism, and procurement-grade collateral. We do not replace the research team. We sit alongside and ship the buyer-readable translation layer. We do not replace existing DevRel hires. We feed them the cookbook arc, the model-card upgrade, and the conference talk brief. We do not replace the PR firm. We coordinate so press hits land alongside AISO citation lift, not in isolation. One weekly receipt for the lab leadership, three audiences served on one spine.

The brand line

Stop publishing into the paper graveyard.
Compound the research edge.

30/60/90 cadence. Research-to-revenue spine signed by day 21. AISO citation work running from week two. Qualified-view proof from week six. Built for foundation-model labs that need developer evangelism plus enterprise pipeline plus buyer-LLM citation, not press-clipping theatre. Pair the seat with Answer Engine Optimization, Perplexity SEO, DevRel, Marketing Foundation, or Podcast depending on the lab's stage and release cadence. Application-layer AI startups route to AI Startups (different ICP axis). Browse all FORKOFF ICPs if a foundation-model lab is not the closest fit.

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