Floqer's AI Agent Fleet Takes Over B2B Prospect Research

Floqer wants to end the most tedious part of B2B sales. The Halifax-based startup took the Startup Battlefield stage at TechCrunch Disrupt 2026 on Wednesday to pitch an autonomous customer knowledge platform powered by a fleet of AI agents that continuously research sales prospects, enrich records, and track buying signals in real time, according to TechCrunch. The eight-person team says it has already passed $1.2 million in annual recurring revenue with more than 1,000 customers, and it plans to open-source the core technology behind its autonomous database in early 2027.

The pitch lands at a moment when revenue teams are drowning in stale data. Sales representatives still spend hours each week hunting for basic facts about prospects — scanning company websites, professional profiles, and job boards, then chasing contact details that turn out to be outdated. Floqer argues the fix is not another point tool but infrastructure: agents that treat customer knowledge as a living system instead of a static snapshot.

A fleet that never stops researching

The platform works in layers. Users describe the prospects they seek in plain language, and Floqer's agents search across company websites, professional profiles, job postings, and more than 100 third-party data sources to generate lists of matching companies and contacts, as reported by WebProNews. When a verified email or phone number is needed, the system applies a waterfall approach — querying one provider after another until it finds a usable result, rather than relying on any single source of truth.

The real differentiator, according to WebProNews, is what happens after the initial list is built: the agents keep watching. They track job changes, promotions, funding announcements, new hires, website updates, and even public code commits, updating records automatically so CRM data stops rotting. Signals are scored against ideal-customer-profile fit so teams act on what matters instead of drowning in noise. In one customer example, agents monitor more than 40,000 accounts and flag those pushing new infrastructure code — turning generic intent data into precise triggers.

Customers report cutting prospecting time by as much as 70%, a figure that appears across multiple accounts of the launch. Perplexity's head of enterprise operations has said the platform runs the company's go-to-market data, citing enriched signups and coverage at scale — a notable endorsement given that Perplexity is both a customer and a backer. As Floqer's peers build out their own research agents — Clay, Outreach, and Mutiny all now offer agents that pull from dozens of sources — Floqer differentiates through continuous monitoring and CRM data hygiene at scale, as reported by WebProNews.

From Chrome extension to autonomous knowledge base

Floqer's current product looks nothing like its first. Co-founders Shivam Mahajan, previously a software engineer at Kyndryl, and Zaaheda Islam, formerly a senior data scientist at Axis Capital, met at university and started in 2024 with a Chrome extension called Super Chat that let users take notes through their ChatGPT accounts, according to TechCrunch. Enterprise users began repurposing the extension to clean data in their CRM systems, and the founders pivoted when they saw that keeping CRM data clean was mostly manual work with few established processes.

As BetaKit detailed, the team came to believe that distribution — not product velocity — was the real bottleneck for many companies, a view reported by WebProNews. Floqer now sits atop existing CRMs such as Salesforce and HubSpot with no row limits and no per-seat pricing, positioning itself as the infrastructure layer that keeps customer data accurate and ready for AI-driven go-to-market motions.

The numbers suggest the pivot landed. Floqer announced a $2 million pre-seed round in July 2026 backed by Perplexity's F7 Fund, N49P, Tidal Venture Partners, and Perplexity co-founder Denis Yarats, according to the company's Business Wire announcement. Less than two years after founding, the startup says it is well past the seven-figure ARR mark, cash-flow positive, and serving more than 1,000 organizations — including Wise and AngelList — while its agents have cleaned more than 10 million records. Mahajan told Business Wire that product velocity stopped being the bottleneck; customer understanding is, with buyer signals scattered across systems now flowing into one scored view.

The approach connects to a broader pattern in the agent economy: Floqer's fleet resembles the oversight challenges startups are racing to solve. Analysts note that agent guardrails and monitoring are becoming table stakes as fleets like this one gain autonomous access to company systems — and the same agent-driven pattern is reshaping customer-facing operations across industries.

Open-sourcing the database in early 2027

Floqer's most distinctive move may be its decision to open-source the autonomous database technology. According to TechCrunch's report on the Disrupt pitch, the startup targets early 2027 for the release, pending security reviews. Many startups guard their models and data pipelines; Floqer bets that enterprises with strict data-residency rules or compliance requirements will prefer to self-host and customize, inviting contributors to strengthen the agent fleet in the process.

Challenges remain. Data accuracy still depends on the quality of public sources and third-party providers, privacy regulations tighten yearly, and enterprises worry about feeding sensitive CRM records into external systems — which makes the open-source path strategically timed, as reported by WebProNews. And while 70% time savings sounds impressive, actual gains vary by sales motion and data maturity.

Floqer's pitch underscored a shift already underway: B2B revenue operations are becoming less about manual list building and more about orchestrating fleets of specialized agents. The companies that treat customer data as continuously updated intelligence gain measurable speed; others risk falling behind as competitors act on fresher signals. Whether the open-source release delivers customization without security trade-offs will shape the next chapter. For now, the metrics impress, the customer list grows, and revenue teams that once budgeted hours for prospect research suddenly have those hours back. The agents keep researching — the humans get to sell.