We audited the marketing at Apex.AI
The safety-certified software infrastructure powering autonomous mobility. Here's what we found and what we'd build for you.
Jan, this page was built using the same AI infrastructure we deploy for clients.
Month-to-month. Cancel anytime.
Deep technical credibility, but no visible demand generation engine to convert market interest in SDVs into qualified pipeline
Founder authority is underleveraged on LinkedIn, where every automotive CTO and VP Engineering makes vendor decisions
Low AI citation visibility for safety-certified middleware queries across LLMs where engineering leaders now research toolchains
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Apex.AI's Leadership
We mapped your current team to understand where MH-1 fits in.
MH-1 doesn't replace your team. It becomes your marketing team: dedicated humans + AI agents running execution at scale while you focus on product development and closing OEM deals.
Here's Where You Stand
World-class product and strategic investors, but significant gaps in demand generation, thought leadership, and AI-era visibility.
Apex.AI has a category-defining product with $87.5M in funding from Volvo, Continental, Toyota Ventures, and Lightspeed. Marketing infrastructure is minimal relative to the commercial opportunity ahead. Post-Series B is the right time to build this.
Website covers product pages (Apex.Grace, Apex.Ida) and press, but lacks deep technical content. Engineering leaders searching "safety-certified ROS 2," "ASIL D middleware," or "SDV software stack" likely land on competitors or open-source forums first.
MH-1: SEO Engine builds a technical content moat around "safety-certified automotive middleware," "ROS 2 production," and "software-defined vehicle infrastructure" queries.
When automotive engineers ask ChatGPT or Perplexity for "best autonomous driving middleware" or "safety-certified vehicle OS," Apex.AI needs to be cited. Currently, Applied Intuition and AUTOSAR references dominate.
MH-1: AEO Agent audits AI citation visibility weekly across 6 LLMs and builds content designed to increase Apex.AI's presence in AI-generated technical recommendations.
No visible paid demand generation. Enterprise sales appears entirely relationship-driven through investor networks and industry events. No paid layer to fill top of funnel or accelerate pipeline beyond warm intros.
MH-1: Creative Generator produces LinkedIn ad variants targeting VP Engineering, ADAS leads, and platform architects at OEMs and Tier-1s. Analytics Agent optimizes by company tier and role.
Blog has product updates and partnership announcements. Jan Becker is a Stanford lecturer and MotorTrend SDVI awardee, but that authority is not consistently channeled into LinkedIn thought leadership or long-form content for the SDV buyer.
MH-1: LinkedIn Ghost-Writing agent builds Jan's profile as the definitive voice on safety-certified autonomous systems. Newsletter agent curates weekly SDV market intelligence.
With Continental, Volvo, Jaguar Land Rover, ZF, AGCO, and Daimler Truck as strategic investors and customers, expanding usage across divisions within these accounts is likely the fastest revenue path. No visible automated expansion motion.
MH-1: Lifecycle Optimizer builds developer onboarding sequences, cross-division expansion triggers, and champion nurture programs across your OEM and Tier-1 accounts.
Top Growth Opportunities
When automotive CTOs ask AI assistants for SDV software stacks, Apex.AI should be the first name cited. Applied Intuition and open-source AUTOSAR currently dominate these responses. This is the new SEO for developer infrastructure companies.
AEO Agent → weekly citation audit across ChatGPT, Perplexity, Gemini, Claude + targeted technical content strategy
Stanford lecturer, Bosch alum, MotorTrend SDVI of the Year. The credibility is there but the content engine is not. LinkedIn thought leadership drives enterprise pipeline in B2B automotive software, where every deal involves a 6-12 month technical evaluation.
LinkedIn Agent → 4 posts/week in Jan's voice on automotive safety, SDV architecture, and the future of mobility software
Continental, Volvo, JLR, ZF, AGCO, and Daimler Truck are investors and early adopters. Each has dozens of vehicle programs and divisions. Automated expansion campaigns could 3-5x revenue from existing logos without a single cold outreach.
Lifecycle Agent → usage triggers, champion identification, developer onboarding sequences, technical briefing content for new divisions
3 Humans + 7 AI Agents
A dedicated marketing team built specifically for Apex.AI. The humans handle strategy and judgment. The AI agents handle execution at scale.
Human Experts
Owns Apex.AI's growth roadmap. OEM pipeline strategy, account expansion playbooks, board-ready reporting. Translates developer adoption signals into revenue. Experienced with complex B2B sales cycles in automotive.
Runs LinkedIn Ads targeting VP Engineering, ADAS leads, and platform architects at OEMs and Tier-1 suppliers. Manages creative testing, budget allocation, and pipeline attribution by account tier.
Builds Jan Becker's thought leadership on LinkedIn. Creates technical content on safety-certified SDV development. Manages the content-to-pipeline engine across automotive engineering audiences.
AI Agents
Monitors AI citation visibility across 6 LLMs weekly. Builds content targeting "safety-certified middleware," "ROS 2 production," "autonomous vehicle OS," and SDV infrastructure queries.
Produces LinkedIn ad variants targeting automotive CTOs, ADAS engineers, and platform leads. Tests headlines, visuals, and technical value props at 10x the speed of manual production.
Builds lifecycle sequences: developer onboarding, cross-division expansion triggers, champion nurture, and re-engagement for accounts with stalled evaluations.
4 posts/week in Jan Becker's voice on safety-certified systems, SDV architecture, and autonomous mobility. Builds the founder narrative that drives enterprise inbound from senior OEM decision-makers.
Tracks competitors (Applied Intuition, Wind River, AUTOSAR ecosystem, Elektrobit). Monitors positioning changes, partnership announcements, content strategy, and developer community activity.
Attribution by OEM tier, channel performance, pipeline velocity. Catches budget waste automatically. Weekly synthesis reports with board-ready metrics.
Weekly SDV market intelligence digest: regulatory changes, OEM program announcements, safety certification updates, competitor launches. Positions Apex.AI as the intelligence layer for automotive software leaders. Drives inbound pipeline from subscribers.
Active Workflows
Here's what the MH-1 system would be doing for Apex.AI from week 1. Every output is an experiment. Every experiment feeds a playbook.
Every Monday: audit Apex.AI's visibility across ChatGPT, Perplexity, Gemini, Claude for 25+ queries like "best autonomous driving middleware," "ASIL D vehicle OS," and "ROS 2 production framework." Track citation rate changes. Generate targeted content to fill gaps.
4 posts/week from Jan's profile. Signal-driven topics: UNECE regulation updates, OEM platform shifts, ISO 26262 certification insights, SDV architecture decisions. Each post builds authority with the automotive engineering buyer.
Generate 20+ ad variants per sprint targeting VP Engineering, ADAS leads, and software platform owners at OEMs and Tier-1s. A/B test technical messaging, value props, and offers. Automatically promote winners and kill underperformers.
Track engagement patterns across your strategic investor accounts (Continental, Volvo, JLR, ZF, AGCO, Daimler Truck). Trigger expansion sequences when new vehicle programs launch. Build champion programs to drive cross-division adoption.
Weekly scan of Applied Intuition, Wind River, Elektrobit, and the AUTOSAR ecosystem. Track partnership announcements, developer tool launches, and messaging pivots. Inform Apex.AI's competitive positioning in real time.
Weekly synthesis: which channels drive pipeline, which content resonates with OEM buyers, where budget is wasted. Board-ready metrics with AI-generated recommendations. The system gets smarter every cycle.
Traditional Marketing vs. MH-1
Traditional Approach
MH-1 System
Audit. Sprint. Optimize.
3 phases. Real output every 2 weeks. You see results, not decks.
AI Audit + Growth Roadmap
Full diagnostic of Apex.AI's marketing infrastructure: SEO, AEO visibility, paid, content, lifecycle. Prioritized roadmap tied to OEM pipeline metrics and developer adoption KPIs. Delivered in 7 days.
Sprint-Based Execution
2-week sprint cycles. Sprint 1 ships AEO content targeting "safety-certified middleware" queries + LinkedIn thought leadership for Jan Becker. Sprint 2 adds paid LinkedIn campaigns targeting VP Engineering at OEMs. Real campaigns, not presentations.
Compounding Intelligence
AI agents monitor your channels 24/7. They catch budget waste, detect creative fatigue, track AI citation changes, and run A/B experiments autonomously. Week 12 is measurably better than week 1.
AI Marketing Operating System
3 elite humans + AI agents operating your growth system
Output multiplier: ~10x output at a fraction of the cost. The system gets smarter every week.
Month-to-month. Cancel anytime.
Common Questions
How does MH-1 differ from a marketing agency?
MH-1 pairs 3 elite human marketers with 10 AI agents. The humans handle strategy, creative direction, and judgment calls. The AI agents handle execution at scale: generating ad variants, monitoring competitors like Applied Intuition and Wind River, building developer nurture sequences, tracking citations across LLMs, running A/B experiments autonomously. You get the quality of a senior marketing team with the output volume of a 15-person department.
What kind of results can we expect in the first 90 days?
Week 1: Full audit and roadmap. Weeks 2-4: First sprint ships AEO content targeting "safety-certified vehicle middleware" and "ROS 2 production framework" queries, plus LinkedIn thought leadership for Jan. Weeks 4-8: Second sprint adds paid LinkedIn campaigns targeting VP Engineering at OEMs and Tier-1s, plus lifecycle expansion sequences for your strategic investor accounts. By day 90, all AI agents are running, you have measurable pipeline attribution, and the system is compounding.
What does "AI citation visibility" mean for Apex.AI?
When an automotive CTO asks ChatGPT, Perplexity, or Gemini "what's the best safety-certified middleware for autonomous vehicles," the LLM cites specific products. Our AEO Agent monitors how often Apex.AI appears in those responses across 6 major LLMs and builds content specifically designed to increase your citation rate. This is the next SEO, and it matters especially for developer infrastructure where engineering leaders increasingly use AI to evaluate vendor options before entering a formal RFP.
Do you understand B2B automotive software sales cycles?
Yes. We know that OEM software procurement involves 6-12 month evaluations, multiple stakeholders (engineering, purchasing, safety, program management), and that content needs to address ASIL certification, real-time determinism, and integration with existing architectures. Our Growth Strategist has deep-tech B2B experience, and the AI agents are tuned for long-cycle enterprise pipeline, not SaaS-style quick conversions. The system is built to accelerate the evaluation phase, not skip it.
Can we cancel anytime?
Yes. MH-1 is month-to-month with no long-term contracts. We earn your business every sprint. That said, compounding effects kick in around month 3 as the AI agents accumulate data and the system learns what works for Apex.AI specifically. In automotive software, where deal cycles are longer, the intelligence compounds especially well because the system builds a deep understanding of which content and channels influence specific OEM buyer personas over time.
You build the software that moves vehicles. Let's build the system that moves your pipeline.
The system gets smarter every cycle. Let's talk about building it for Apex.AI.
Book a Strategy CallMonth-to-month. Cancel anytime.