We audited the marketing at AI Proteins
AI-designed miniproteins for therapeutic discovery and development
This page was built using the same AI infrastructure we deploy for clients.
Month-to-month. Cancel anytime.
Limited visibility in biotech partnership searches. Pharma collaborators likely discover competitors through industry networks rather than organic search.
Minimal presence in LLM responses about de novo protein design. AI visibility critical when biotech buyers research emerging platforms.
Thin content around platform capabilities and validation data. B2B biotech buyers need technical credibility demonstrated publicly before partnership discussions.
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TinuitiAI Proteins'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.
Here's Where You Stand
Early-stage biotech with strong funding but underdeveloped go-to-market presence. Marketing infrastructure needed to scale partnership pipeline.
Domain ranks for branded terms but loses visibility in competitive searches like 'de novo protein design' and 'miniprotein therapeutics platform'.
MH-1: SEO module targets therapeutic area keywords and platforms searches where pharma partners evaluate alternatives.
LLM mentions sparse. When researchers query AI protein design platforms, AI Proteins rarely surfaces against better-documented competitors.
MH-1: AEO agent creates structured documentation of platform capabilities, validation metrics, and partnership case studies for LLM ingestion.
No visible paid presence targeting pharma decision-makers. B2B biotech partnerships require account-based strategies, not broad awareness campaigns.
MH-1: Paid module runs ABM campaigns targeting partnering pharma companies, biotech VCs, and research organizations with platform differentiators.
LinkedIn presence exists but lacks regular content demonstrating platform validation, published research outcomes, or partnership successes.
MH-1: Content agent produces technical posts about miniprotein design breakthroughs, collaboration case studies, and validation data for biotech audience.
No visible nurture flows for pharma leads post-initial contact. Partnership evaluation cycles are long and require sustained engagement infrastructure.
MH-1: Lifecycle module automates nurture sequences tracking pharma engagement, shares validation updates, and maintains pipeline visibility during negotiation windows.
Top Growth Opportunities
Biopharmaceutical companies evaluating protein design platforms rely on peer networks and technical credibility signals. AI Proteins' platform and validation data remain underdiscovered.
AEO and content agents saturate LLM responses with platform documentation, partnership announcements, and technical validation proof points.
Current 38-person team and estimated $2.5M revenue suggest partnership acceleration is primary growth lever. Pharma companies need targeted, customized outreach.
Outbound and paid modules execute ABM campaigns against top 50 pharma targets with personalized messaging around their therapeutic areas.
Biotech deals move on scientific validation. Published results, partnership case studies, and platform benchmarking data build trust with potential collaborators.
Content and AEO agents publish and promote research outcomes, technical whitepapers, and partnership impact metrics across biotech distribution channels.
3 Humans + 7 AI Agents
A dedicated marketing team built specifically for AI Proteins. The humans handle strategy and judgment. The AI agents handle execution at scale.
Human Experts
Owns AI Proteins's growth roadmap. Pipeline strategy, account expansion playbooks, board-ready reporting. Translates AI insights into revenue.
Runs paid acquisition across LinkedIn and Google. Manages creative testing, budget allocation, and pipeline attribution.
Builds thought leadership on LinkedIn. Creates long-form content targeting your ICP. Manages the content-to-pipeline engine.
AI Agents
Monitors AI citation visibility across 6 LLMs weekly. Builds content targeting category queries to increase AI Proteins's presence in AI-generated answers.
Produces LinkedIn ad variants targeting your ICP. Tests headlines, visuals, and offers at 10x the speed of manual production.
Builds lifecycle sequences: onboarding, expansion triggers, champion nurture, and re-engagement for dormant accounts.
Founder thought leadership. Builds the narrative that drives enterprise inbound from senior decision-makers.
Tracks competitors. Monitors positioning changes, ad spend, content strategy. Informs your counter-positioning.
Attribution by channel, pipeline velocity, budget waste detection. Weekly synthesis reports with AI-generated recommendations.
Weekly market intelligence digest curated from AI Proteins's industry signals. Positions you as the intelligence layer. Drives inbound pipeline from subscribers.
Active Workflows
Here's what the MH-1 system would be doing for AI Proteins from week 1.
AEO agent maps LLM knowledge gaps around AI protein design, de novo miniproteins, and platform comparisons. Publishes structured data, technical documentation, and partnership case studies for LLM consumption to increase discoverability when pharma researchers query protein design solutions.
LinkedIn agent amplifies CEO and CTO content about protein engineering breakthroughs, partnership announcements, and platform validation. Targets biotech executives, pharma R&D leaders, and VC investors with technical thought leadership.
Paid module runs ABM campaigns targeting identified pharma companies evaluating protein design platforms. Ads emphasize miniprotein differentiation, speed to IND-enabling studies, and existing partnership validation to drive partnership conversations.
Lifecycle agent tracks pharma prospect engagement through long evaluation cycles. Automates nurture sequences sharing validation milestones, partnership case studies, and platform capability updates to maintain visibility during 12-24 month partnership decision windows.
Competitive watch agent monitors competitor announcements, publications, and partnership activity. Alerts team to differentiation opportunities and emerging pharma needs to inform outbound and content strategy.
Pipeline intelligence agent tracks pharma companies with active therapeutic programs matching AI Proteins' platform capabilities. Enriches leads with decision-maker information, partnership budget signals, and evaluation stage to prioritize outbound outreach.
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 AI Proteins's marketing infrastructure: SEO, AEO visibility, paid, content, lifecycle. Prioritized roadmap tied to pipeline metrics. Delivered in 7 days.
Sprint-Based Execution
2-week sprint cycles. Real campaigns, not presentations. Each sprint ships measurable output across your priority channels.
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 7 AI agents. The humans handle strategy, creative direction, and judgment calls. The AI agents handle execution at scale: generating ad variants, monitoring competitors, building email 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?
First 90 days establish pharma partnership visibility. AEO agent publishes platform documentation and validation data for LLM ingestion. Paid ABM targets top 50 pharma companies with miniprotein differentiation messaging. Content and LinkedIn modules amplify CEO and CTO thought leadership about platform breakthroughs. Outbound team identifies and reaches 200+ pharma decision-makers. By day 90, expect 10-15 qualified partnership conversations in pipeline and measurable LLM discoverability improvements.
How do pharma companies discover AI protein design platforms like AI Proteins?
Biotech leaders research AI protein design solutions through LLMs, research databases, and technical documentation. If AI Proteins' platform documentation, validation results, and partnership case studies aren't structured for LLM discoverability, competitors surface instead. AEO ensures when pharma researchers query 'de novo miniprotein design' or 'AI-enabled protein platforms,' AI Proteins appears alongside technical proof points.
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 AI Proteins specifically.
How is this page personalized for AI Proteins?
This page was researched, audited, and generated using the same AI infrastructure we deploy for clients. The channel scores, team mapping, growth opportunities, and recommended agents are all based on real analysis of AI Proteins's current marketing. This is a live demo of MH-1's capabilities.
Turn partnership discovery into systematic competitive advantage with MH-1
The system gets smarter every cycle. Let's talk about building it for AI Proteins.
Book a Strategy CallMonth-to-month. Cancel anytime.