Machina

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Marketing thatwins theshortlist.

AI Marketing Agency

Buyers burned by a failed pilot discount the next set of claims. MIT found no measurable P&L return in 95% of enterprise pilots. We market AI companies on evidence a skeptic can check: published benchmarks, a demo before the sales call, a security page the CISO forwards. One AI content-review platform went from $12K to $208K MRR in six months.

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Modern data center aisle with shallow depth of field: rows of server racks with soft blue-green status glow fading into darkness, single warm light source

What makes AI different

Selling AI in the year after the pilots failed

The SEC began charging companies over AI-washing in 2025. A claim you cannot document is legal exposure now, on top of a credibility problem. Close to half of global venture funding went into AI, which means thousands of funded rivals open with your adjective. MIT found no measurable P&L return in 95% of enterprise pilots. Security review stretches deals to 6–10 months, and AI/ML keywords cost $6.91 a click. A plan that ignores any of that stalls by month three.

What we hear

What AI founders tell us on the first call

Four objections that come up on nearly every first call with a technical founder.

Every competitor's homepage says the same two words: AI-powered

Close to 50% of 2025 venture funding went into AI, so the adjective cannot carry your positioning. The SEC now prosecutes AI-washing on top of that. The web development work has to argue: a demo above the fold, published benchmarks, pricing in the open, and a security page the CISO can forward.

Web Development

Our buyers ask ChatGPT for recommendations, and it never mentions us

The assistant is now writing the shortlist your sales team used to influence, and 94% of buying groups rank one before they contact anyone. Our SEO work aims at what gets quoted: comparison pages, integration pages, and benchmark numbers with the method attached. ChatGPT-referred visitors convert at 2.4% for B2B SaaS against roughly 1.8% from organic search.

SEO

Google Ads burns runway faster than it fills pipeline

AI/ML keywords cost $6.91 a click, the priciest category in search. Non-branded B2B costs jumped 29% in 2025. So paid ads only buy intent that exists already: competitor comparison queries, category-plus-compliance terms, and LinkedIn ABM aimed at the whole buying committee.

Paid Ads

Enterprise deals go quiet for months between security review and procurement

The average B2B cycle ran 10.1 months in 2025. Your champion argues your case alone through most of that silence. Email marketing is how you stay in the argument: pilot-stakeholder sequences that hand them the ROI proof a CFO will ask for, and changelog sends that keep your shipping speed visible.

Email Marketing

What we do

Five services, and the AI economics behind each

CAC payback, trial-to-paid, citation share, cycle length. An AI founder reports those to the board, so each service below is scoped against them.

Web Development

An evaluator judges your engineering by your marketing site long before they open your docs. So the site carries the proof: a demo or sandbox above the fold, docs one click from the homepage, pricing in the open, a security page covering SOC 2 and data handling, and a public changelog. It loads in under a second on Next.js, with structured data and llms.txt in place. 94% of buying groups rank a shortlist before they contact anyone.

SEO

Two indexes now, one job. Ranking on Google still pays, and so does getting quoted by ChatGPT, Claude, and Perplexity. AI-referred traffic converts at 2.4% for B2B SaaS against roughly 1.8% from organic, and Seer Interactive measured one B2B client at 15.9%. We publish what the engines pick up: comparison pages, integration pages, a use-case page per ICP, and benchmark content with real numbers. The day-one shortlist favorite wins 80% of deals.

Paid Ads

AI/ML keywords average $6.91 per click, the priciest category in search. Non-branded B2B CPCs rose 29% to $5.34 in 2025. With median CAC payback already at 18 months, awareness spend cannot pay itself back. So we buy bottom-funnel only: competitor and comparison queries, category-plus-compliance terms like enterprise RAG platform SOC 2, LinkedIn ABM sequenced to the evaluator, the budget owner and the CISO, and retargeting pools built from docs and pricing visitors. Every dollar reports to pipeline.

Email Marketing

Two different clocks, both of them run on email. Enterprise AI deals take 6–10 months, and a PLG trial goes cold in days. We build activation sequences tied to time-to-first-value. We add pilot-stakeholder nurture that hands your champion the ROI proof the CFO will demand, and changelog emails that keep your shipping speed visible. Lifecycle flows run 30.6% opens and 7.4% click-through, against 20.7% and 2.3% for one-off blasts.

AI Automation

The pattern we fix most often is an AI company running its own go-to-market by hand. We wire lead scoring and enrichment into your CRM, and route PLG signals to sales the moment they fire (docs deep-dives, API key creation, pricing visits). We draft GEO content from your own docs and release notes, then automate reporting from ad click to closed-won. One client's lead response fell from 48 hours to 5 minutes on this stack.

Who we work with

Who we work with

Sub-niche by sub-niche, the buyer changes, and so does the plan.

Developer tools & AI infrastructure

PLG products bought by engineers who block ads and trust peers: 84% use AI tools, 46% distrust the output. The plan runs on docs, free tiers, open source, and engineering content that admits trade-offs.

Enterprise AI platforms

6–10 month cycles through security review, legal, and procurement. Marketing arms the champion: SOC 2 documentation, ROI evidence, reference customers, and a pilot structure that limits downside.

Agtech & robotics AI

Reservoir Farms opened the world's first on-farm robotics incubator in Salinas in 2025, backed by John Deere, Driscoll's, and Taylor Farms. Selling AI to growers takes field-level ROI, not model cards. That translation is our home turf.

Open-source & open-core AI

The community is the funnel: GitHub, Hacker News, Discord. We build the commercial layer around it, from repo to paid conversion paths, without burning the trust the project earned.

AI-enabled vertical SaaS

AI sold into non-tech industries: insurance claims, ecommerce support, crop monitoring. These buyers search their problem, not your architecture, so the keyword map starts with their vocabulary.

AI visibility

AI Search Visibility for AI Companies

There is an irony in this category. You sell AI, and your buyers now ask AI which vendor to trust. ChatGPT referral traffic grew 206% year over year into 2026, and those visitors convert at 2.4% for B2B SaaS, because the assistant already made your argument for you. The engines build that argument from answer-first HTML, and most AI startup sites fail there: the benchmarks, the pricing, and the security page all render in JavaScript the crawlers never run. We move that proof into readable markup and publish an llms.txt to match. You can grade your own retrievability in a few minutes with the free SEO report.

$2.5M

ARR in six months. AI content-review platform, $150K budget.

95%

of enterprise AI pilots show no P&L return (MIT, 2025)

85%

trial-to-paid conversion we built for an AI content-review platform

Your buyer ranks the shortlist before you know they exist, and the vendor in first place wins 80% of the time. The sales call you're rehearsing has already happened.

Case study

From $12K to $208K MRR in six months, on a $150K budget

An AI content-review platform came to us with a strong product and the category's standard problem: every competitor made the same claims, and buyers had no reason to believe any of them. We repositioned the launch around proof. ROI calculators, product sandboxes, and case demos made the technology tangible before any sales call; 50+ technical content pieces and 15 webinars built the evidence layer underneath. Multi-touch attribution tracked every touch, with LinkedIn driving 42% of conversions, content 28%, and partner channels 19%, so the budget followed what converted instead of what felt visible. Six months later: monthly active users up 300%, from 2,400 to 9,600, and MRR up from $12K to $208K, $2.5M in ARR. Trial-to-paid conversion held at 85%, which tells you the demand was qualified, not bought.

Read the case study
$12K → $208K
MRR in six months
The launch exceeded our expectations. The strategic approach and execution delivered results that transformed our market position.
Sarah Chen, VP of Product · AI-Powered Shoppable Video Platform

The Day-One Shortlist

How we work

The Day-One Shortlist: three phases, one goal. Be the vendor ranked first before the first conversation.

01

Audit the evidence

A free audit of how buyers find and judge you: Google rankings, whether ChatGPT and Perplexity cite you, what your site proves versus what it claims, and where trials or pilots stall. Most AI startups fail the citation check before the content check, so we measure both.

02

Build the proof layer

Comparison pages, benchmark content, and use-case pages per ICP go live alongside the site work: demo above the fold, security page, transparent pricing. Bottom-funnel paid and LinkedIn ABM fill pipeline now while the organic and citation layers compound underneath.

03

Automate the long cycle

Lifecycle sequences tied to time-to-first-value keep trials warm; pilot-stakeholder nurture carries the 6–10 month enterprise deal. Attribution runs from first click to closed-won, so you always know which channel earned the revenue and which one borrowed the credit.

Playbook

The AI Marketing Playbook

AI companies raised $202.3 billion in 2025, close to half of all venture funding worldwide, with 58% of it landing in megarounds of $500M or more (Crunchbase). Every dollar of it funds a competitor making your claims. Ten tactics we run for AI and deep-tech startups, each with the math attached.

01

Win the shortlist before the first conversation exists

B2B buyers complete about 61% of their evaluation before contacting a vendor, 94% of buying groups rank a shortlist before reaching out, and the vendor ranked first on day one wins roughly 80% of the time (6sense, 2025). Read that as a budget instruction: most of your marketing has to work in rooms you are not in. Build comparison pages for every rival that shows up in your deals, a use-case page per ICP, integration pages for the stack your buyers already run, and pricing they can find without booking a call. The website has to close the evaluation gap alone, because by the time the demo request arrives, the decision is mostly made.
02

Publish the benchmark your competitors are afraid of

MIT's GenAI Divide report found 95% of enterprise generative AI pilots produce no measurable P&L impact, despite $30–40 billion in enterprise spend (2025). Your prospects either lived that failure or read the headline, and the SEC's 2025 AI-washing enforcement means inflated claims now carry legal risk. Argue with evidence a skeptic can check: published benchmarks against named alternatives, a live demo that runs without a sales call, case studies with real numbers, and an honest page about where the product does not fit. The startup willing to show its failure modes reads as the one telling the truth, and in a category short on trust, that is the position worth owning.
03

Treat ChatGPT like a search engine with a 2.4% conversion rate

ChatGPT-referred traffic converts at 2.4% for B2B SaaS (First Page Sage, 2026) against roughly 1.8% for organic search, and Seer Interactive measured one B2B client converting ChatGPT visitors at 15.9% versus 1.76% from Google organic. Volume is still small; the visitors arrive pre-qualified because the assistant already argued your case. Getting cited takes answer-first structure: a 40–60 word direct answer under every major heading, one attributed statistic every 150–200 words, comparison and use-case pages, consistent entity data, and llms.txt. It also takes server-rendered HTML, because AI crawlers do not execute JavaScript. Proof locked inside client-side components never gets quoted, no matter how good it is.
04

Write one page for each of the three people who can kill your deal

An enterprise AI purchase runs through an ML engineer who evaluates the API, a VP who owns the budget, and a CISO who runs the security review, and each one rejects a different kind of content. The engineer wants docs, latency numbers, and a sandbox. The VP wants payback period, hours saved, and a reference customer in their industry. The CISO wants SOC 2 Type II, data handling, and model-provider disclosure. Most AI startup sites speak only to the founder's mirror image, the technical evaluator, and lose the other two votes without ever hearing the objection. We build a content path for each: technical depth, a business case, and a trust center.
05

Earn the channels you cannot buy

Stack Overflow's 2025 survey: 84% of developers use AI tools, 46% actively distrust their accuracy, and only 3% highly trust the output. These are your evaluators. They block ads, and over half of dev-tool discovery happens in private Slack and Discord communities and peer recommendations, places no media budget reaches. The tactics that work are the slow ones: useful open-source releases, engineering posts that admit trade-offs, answering questions where practitioners ask them, and launch moments on Hacker News and Product Hunt that seed word of mouth. A founder explaining a design decision in plain terms outperforms any brand campaign in this category, which is why we ghost-produce founder content instead of brand copy.
06

Make time-to-first-value the conversion metric

61% of B2B buyers prefer a rep-free experience (Gartner, 2025), and after the AI-washing era, a working product is the only claim buyers believe. Free tier, sandbox, or interactive demo: pick the one your product supports and instrument it, then shorten the path from signup to the first moment of proof. We ran this play for a SaaS platform and halved time-to-first-value from 14 days to 7; onboarding completion rose from 61% to 92% and monthly churn fell 45%. For a PLG AI product, the first successful API call or the first useful output is the sales meeting. Point the whole site at it.
07

Spend paid dollars only where intent already exists

AI and ML keywords average $6.91 per click, the most expensive premium category WordStream tracks, and non-branded B2B search CPCs rose about 29% to $5.34 in 2025 (Dreamdata). With median CAC payback for $5M–$50M ARR SaaS companies already at 18 months (High Alpha, 2025), broad awareness spend is a furnace. The paid budget goes four places: competitor comparison queries, category-plus-compliance terms like "enterprise RAG platform SOC 2," brand defense, and LinkedIn ABM sequenced to the full buying committee, with retargeting pools built from docs and pricing-page visitors. Everything else waits until the organic and community layers prove which messages convert.
08

Nurture the ten-month cycle or lose it in month three

The average B2B sales cycle ran 10.1 months in 2025 (6sense), and an AI deal adds security review and procurement on top. Your champion carries the deal through months of internal silence, and most vendors leave them unarmed. Automated lifecycle flows run 30.6% opens and 7.4% click-through against 20.7% and 2.3% for one-off blasts (ActiveCampaign). Build three sequences: trial activation tied to time-to-first-value, pilot-stakeholder nurture that hands your champion the ROI evidence the CFO will demand, and a changelog email that turns your shipping velocity into a monthly argument for keeping you ranked first. The deal you closed in month ten was saved by the email in month four.
09

Translate the model into field-level ROI

The Bay Area took roughly 60% of global AI venture funding in 2025, $126 billion, and California companies captured about 80% of US AI rounds (Crunchbase). An hour south of that noise, the Central Coast builds applied AI: Reservoir Farms opened the world's first on-farm robotics incubator in Salinas in 2025, 40 acres backed by John Deere, Driscoll's, Taylor Farms, Tanimura & Antle, and Western Growers; UC Santa Cruz runs an AgTech Alliance; DART organizes the Monterey Bay robotics ecosystem; Joby Aviation builds in Marina. These companies sell to growers and operators, not to other AI companies. The marketing that works here translates deep tech into acres covered, hours saved, and payback per season. That translation is the work we do all day.
10

Report pipeline, not impressions

Funnel benchmarks for mature B2B teams: 1–3% of website visitors become leads, 10–15% of leads become opportunities, and 20–30% of opportunities close (Stackmatix, 2025). Instrument every stage, because in a 6–10 month cycle the channel that gets credit is usually the last click, while the channel that did the work is the content someone read in month one. Multi-touch attribution on the AI-powered AI platform launch we ran showed LinkedIn driving 42% of conversions, content 28%, and partner channels 19%; without that report, the content budget gets cut first and pipeline dries up two quarters later. Attribution is the difference between cutting the right budget and cutting the cheapest one.

AI & Deep Tech

Let's win your shortlist before the next megaround buys your category's attention

Start with a free audit. We'll pull your Google rankings, check whether ChatGPT and Perplexity cite you, and score what your site proves against what it claims. Twenty minutes, no obligation.

Free audit first No long-term contracts Based in Hollister, California. Working nationwide.

Last updated July 4, 2026