Martech startup Floqer raises £1.5m backed by the Perplexity fund and N49P
This article covers Floqer, a martech startup that has raised £1.5m in a pre-seed funding round to build an autonomous customer knowledge base. The development aims to support sales and product teams by joining public and private customer data to surface high-intent prospects and targets martech and go-to-market functions across the UK and European startup ecosystem.
Floqer, a martech startup, has raised £1.5m in a pre-seed funding round to build what it calls an autonomous customer knowledge base that joins public and private data to help go-to-market teams identify and reach high-intent prospects. The raise matters because it highlights renewed early-stage investor interest in AI-led tools that make unstructured customer signals actionable for sales and product teams.
Why it matters
Sales and product teams often work with fragmented signals about potential customers: public news, job posts and filings on one side, and private signals in CRMs, Slack and call transcripts on the other. Floqer’s pitch is that large language models finally make it practical to read and connect those signals at scale, turning raw text into pattern-driven insights for targeting and prioritisation.
If those claims hold up in practice, the product could shorten how long it takes for startups to find the right buyers and convert intent into revenue — a useful proposition at a time when investors are looking for monetisable AI use cases rather than exploratory tooling alone. Floqer cites early customers that include Wise (global payments), Perplexity (AI search), AngelList (startup platform) and Pulumi (infrastructure as code), which gives the company a mix of enterprise and developer-facing references.
Inside the product
Floqer ingests more than 100 third-party data sources plus customer-owned data sources (CRM, Slack, call logs) and uses NLP to create a single “living” profile for each account. The company positions the product as a customer knowledge layer that surfaces patterns — for example, hiring trends or product issues that historically preceded deals — and then helps teams find lookalike companies demonstrating similar intent.
Key practical claims in the announcement:
- integration of public and private signals into structured account profiles;
- the ability to query cohorts to surface repeatable buying signals; and
- tooling to operationalise those insights into targeted outreach.
Floqer also shared internal traction metrics: the founders went full-time in October 2024, and the business reports revenue growth of 8x since June 2025. The team has recruited several hires from startup and founder backgrounds to build GTM and engineering capacity.
Who are the investors?
Floqer raised £1.5m in a pre-seed round backed by a mix of angels and early-stage funds. Named backers include Alex Norman (N49P), Kelly Graziadei and Joanna Lee (co-founders of F7 Ventures), the Perplexity fund, Janneta Tabakov, Denis Yarats (CTO and co-founder of Perplexity), Ian Whytock and Jenny Yang.
Investors cited a combination of team strength and early customer traction as reasons to back the company. The Perplexity fund and Denis Yarats signal interest from AI-focused backers, while named angels and smaller funds bring go-to-market and ecosystem experience.
In the announcement, Alex Norman, Partner at N49P and Co-founder of TechTO, said:
a talent-dense spot
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Founder perspective
Shivam Mahajan is CEO and co-founder; Zaaheda is co-founder and CTO. The founders describe building Floqer to reduce manual, time-consuming research across disparate sources. The company has added hires with founder and operator experience: a former YC founder known as Sean, Rupert Donovan as Head of GTM Engineering, Vansh Sood from a consumer app background, and Abdullah Hussein, who joined from Trolley.
In the announcement, Abdullah Hussein, who joined from Trolley, said:
I automated my own job with Floqer. Now I want to help others do the same.
Floqer also named Avish, an intern-turned-engineer now running infrastructure for large request volumes, and Deep, a long-term collaborator, illustrating early-stage emphasis on engineering scale as usage grows. The team is hiring to expand product and sales capabilities.
The bigger picture
Floqer’s raise sits at the intersection of two trends: investors seeking concrete, revenue-oriented AI startups, and growing demand from GTM teams for richer, unified customer intelligence. For martech, that means more competition from firms stitching data and AI into workflow tools, and a higher bar on privacy, data governance and integration reliability.
In the UK and Europe, pre-seed AI and martech deals remain active but selective; investors are looking for clear paths to monetisation and defensible data strategies. Floqer’s early customer roster and the mix of AI-focused and operator investors will be important as it attempts to prove that automated customer profiles translate into predictable revenue gains for buyers.
The outcome will matter beyond one company: if tools that unify private and public signals at scale become standard, the way startups approach lead generation and product-market fit research could shift across the UK and European martech ecosystem.
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