We audited the marketing at Elicit
AI research assistant automating paper analysis and synthesis
This page was built using the same AI infrastructure we deploy for clients.
Month-to-month. Cancel anytime.
As a research automation platform, Elicit has minimal presence in AI/LLM visibility channels where researchers discover tools
Series A company with $31M funding but only 7K LinkedIn followers suggests untapped founder/thought leadership positioning around AI reasoning
Limited evidence of paid acquisition despite targeting knowledge workers who actively search for research efficiency tools
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TinuitiElicit'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
Mid-stage research AI startup with product-market traction but underdeveloped marketing infrastructure across acquisition channels
Likely ranks for research automation queries but minimal content strategy around paper summarization, data extraction, academic workflows
MH-1: SEO agent builds content hub around researcher pain points, academic use cases, methodology guides for synthesis workflows
Minimal optimization for AI assistant discovery channels where researchers ask Claude, ChatGPT for research tools and recommendations
MH-1: AEO agent optimizes for AI-generated answers about research automation, positions Elicit in LLM context windows and knowledge bases
No visible paid search or display campaigns targeting researchers, academics, knowledge workers seeking automation tools
MH-1: Paid agent runs experiments on researcher intent keywords, academic institution targeting, professional network placements
Public benefit mission around AI reasoning is differentiated but not amplified through founder voices or research insights on scaling good thinking
MH-1: Content agent develops thought leadership on AI-assisted reasoning, Trivedi/Smith visibility on research methodology and AI philosophy
Early revenue ($1M estimated) suggests limited expansion workflows to move researchers from trial to enterprise, team adoption workflows
MH-1: Lifecycle agent automates onboarding for research teams, creates expansion playbooks for moving from individual to institutional licenses
Top Growth Opportunities
Researchers actively search for paper summarization, literature review automation, data extraction tools. Minimal paid presence in this high-intent space.
Paid agent targets researcher keywords across Google, LinkedIn, academic networks with use case messaging around synthesis and data extraction
When researchers ask AI assistants about research tools, Elicit lacks optimization to appear in recommendations and generated content
AEO agent optimizes knowledge bases, trains LLM understanding of Elicit's reasoning capabilities and paper analysis features
Most research is team-based but Elicit marketing speaks to individual researchers. Limited messaging for research departments and lab adoption
Lifecycle agent creates team onboarding, maps research workflow value across lab members, builds ROI case for institutional subscriptions
3 Humans + 7 AI Agents
A dedicated marketing team built specifically for Elicit. The humans handle strategy and judgment. The AI agents handle execution at scale.
Human Experts
Owns Elicit'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 Elicit'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 Elicit'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 Elicit from week 1.
AEO agent monitors LLM training data, optimizes Elicit positioning in Claude and ChatGPT knowledge about research automation, triggers content updates when researcher queries shift
Founder LinkedIn agent publishes Trivedi and Smith insights on AI reasoning, research methodology, scaling good thinking, drives researcher discovery and credibility
Paid agent tests researcher intent keywords across Google and LinkedIn, runs experiments on lab manager targeting, measures cost per qualified researcher and team expansion
Lifecycle agent segments users by research stage (individual researcher vs. lab team), triggers onboarding for paper analysis workflows, builds expansion paths to institutional licenses
Competitive watch agent monitors LLM recommendations for similar tools, tracks researcher discussions in academic communities, alerts on positioning gaps Elicit should address
Pipeline intelligence agent analyzes research institutions, labs, and grant programs, builds outbound lists for partnership and institutional adoption, scores accounts by team size and synthesis needs
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 Elicit'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 focuses on capturing researcher intent across search and AI channels while building team expansion messaging. Paid agent tests researcher keywords and lab manager targeting. AEO agent optimizes LLM visibility. Content agent launches thought leadership on reasoning and synthesis. Lifecycle agent creates team onboarding flows. By day 90, Elicit moves from individual researcher acquisition to capturing team and institutional demand.
How does Elicit appear when researchers ask AI tools about research automation
Most researchers discover tools through AI assistants like Claude and ChatGPT. AEO ensures Elicit's paper summarization and synthesis capabilities are optimized in LLM responses. When a researcher asks their AI assistant for tools to extract data from papers or synthesize findings, Elicit positions itself as the answer through optimized knowledge bases and LLM training data.
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 Elicit specifically.
How is this page personalized for Elicit?
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 Elicit's current marketing. This is a live demo of MH-1's capabilities.
Scale Elicit from individual researchers to research teams with autonomous AI-driven marketing
The system gets smarter every cycle. Let's talk about building it for Elicit.
Book a Strategy CallMonth-to-month. Cancel anytime.