When AI began reshaping how people find products and services, most marketing teams took time to catch on. Yes, traffic still came in, rankings held, and dashboards still looked familiar. But quietly, a different system was taking over, one that decided which brands got cited and trusted before users ever clicked a link.
But Collins Tonui and Gideon Ruhara, co-founders of Lantern, noticed the shift and started building for it.
From their vantage point working on Lantern, this Kenya and U.S.-based startup backed by MarlVC, had a front-row seat to the transition, watching ChatGPT, Gemini, and Claude quietly redraw the rules of search visibility.
That gap became Lantern’s starting point.
Building for a search paradigm that never sleeps
It was clear from the start that the speed of AI search had completely outpaced the rhythm of marketing teams. While AI systems update continuously, most marketing teams still run on weekly sprints and lengthy campaign cycles.
In practice, this creates a delay. By the time a visibility drop lands on a dashboard, gets pulled into a report, turned into a brief, written, approved, and published, the window has already closed. Content that once earned citations gradually disappears from relevance because it’s no longer fresh.
That lag, says CEO and Co-founder Gideon Ruhara, points to a deeper issue. “We quickly realized the gap between insight and execution is an infrastructure problem. By the time most teams act, the system has already moved on.”
Instead of building another analytics dashboard, the Lantern team set out to create something more responsive: a system of autonomous marketing agents that track how brands appear in AI search and automatically act on what they find while humans retain final control.
Closing the AI visibility loop
For most SEO and GEO tools, the insights stop at the data layer. They tell you where you rank, what you’re missing, and sometimes what competitors are doing. The work that follows writing, approving, and publishing still falls on your team. Lantern was built to remove that delay.
Its system continuously monitors how a brand appears across AI platforms like ChatGPT, Claude, and Gemini, identifies drops in citation frequency, and automatically generates and updates content to close the gap.
“For years, the workflow has been data, then human interpretation, and finally action,” says CTO and Co-founder Collins. “Lantern shifts this into a direct path from data to decision to execution. When visibility drops, the system doesn’t wait for a team to notice. It responds.” He adds.
How Lantern’s continuous agentic marketing works
At the core is a network of agents working in coordinated loops. A monitoring agent tracks how often a brand appears in AI-generated answers. When citations fall below a defined threshold, a content agent is triggered. It then researches, writes, and prepares new content for publication. Simultaneously, a refresh agent runs in parallel, continuously preventing older pages from losing relevance.
Internally, one finding keeps coming up: freshness matters more than most teams realize. Content that is not actively maintained gradually falls out of rotation, creating what the team describes as a “decay curve”. This is what Lantern’s agents are built to close.
The new layer of marketing infrastructure
What sets Lantern apart is where the automation sits in the marketing workflow. Instead of operating as another analytics or reporting tool, it integrates directly into the systems teams already rely on, from content management platforms like WordPress and HubSpot to analytics dashboards, allowing insights to flow straight into execution without the usual manual handoffs.
Rather than stopping at impressions or rankings, the platform connects AI search performance to downstream outcomes, tracking how visibility across AI systems translates into traffic and, ultimately, revenue. For marketing teams navigating an increasingly fragmented and opaque search ecosystem, that attribution layer is becoming critical.
From a market perspective, Lantern positions itself within the emerging GEO category. Here, the goal is to be cited within AI systems that now influence discovery earlier in the user journey.
While this is still a young space, it’s quickly drawing attention from operators and investors exploring how AI is reshaping the search and content stack.
Speaking on Lantern’s approach, Amarachi Nwachukwu, who works closely with the team through MarlVC’s portfolio support and is involved in growth and go-to-market initiatives, notes that Lantern’s approach is less about adding another layer of analytics and more about compressing execution time.
“What stands out is how deliberately the team has focused on speed, reducing the gap between visibility insights and action to near zero,” she says. “Most traditional marketing stacks aren’t designed to handle that.”
What Comes Next?
“The real shift isn’t about doing more with less people. It’s about designing systems where the output compounds without adding headcount,” Gideon says.
Like many startups emerging from Africa’s growing builder ecosystem, Lantern operates with a deliberately lean team. But what it lacks in headcount, it makes up for in leverage embedded directly into the product.
By automating core parts of the marketing workflow, from research and content creation to optimization and publishing, Lantern compresses what would traditionally require multiple specialized roles into a single continuous system. Work that once moved across teams and timelines now moves through one coordinated flow.
This reflects a broader shift shaping startups globally; smaller teams producing significantly higher output, powered by AI systems that don’t rely on traditional workflows.
Collins further notes, “In a system that never sleeps, waiting might already be the biggest disadvantage. Companies can only effectively compete in this AI-first internet if they are responding faster.” He adds, “They need to update pages before they lose relevance, identify key gaps before competitors fill them, and ultimately rely on systems that operate continuously.”
Lantern is betting that this always-on, agent-driven, execution-focused model will define the next phase of marketing. And that more founders will increasingly adopt systems that remove the lag entirely.
About Lantern
Lantern is a marketing agent for AI search. It monitors your brand across ChatGPT, Gemini, and Claude, then deploys agents that research, write, and publish the content needed to win AI citations. Lantern integrates with existing marketing stacks, including WordPress and HubSpot, and tracks how AI visibility translates into traffic and revenue. It’s backed by MarlVC and operates across the U.S. and Kenya. Learn more at www.asklantern.com.
