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FairMarkIT

Fintech · Boston, United States · Founded 2017

Fairmarkit is a cutting-edge startup that focuses on optimizing the procurement process, specifically targeting what is known as "tail spend." Tail spend refers to the smaller, less strategic purchases that companies make, which can often be overlooked but collectively add up to a significant amount of money. Fairmarkit uses advanced machine learning technology to streamline sourcing, vendor identification, and automated quoting, thereby accelerating the entire bid-to-buy process. The company serves a diverse range of clients, including large enterprises like Blue Cross Blue Shield and Emirates Flight Catering. These clients operate in various industries but share a common need to manage their procurement more efficiently. Fairmarkit operates in the procurement technology market, which is growing rapidly as businesses seek to automate and optimize their purchasing processes. Fairmarkit's business model is based on providing a software-as-a-service (SaaS) platform. Clients subscribe to the platform, which offers tools to manage tail spend more effectively. The platform helps procurement teams source items more easily, identify the best vendors, and automate the quoting process. This not only saves time but also ensures that companies get the best possible prices for their purchases. The company makes money through subscription fees for its platform. Additionally, Fairmarkit may charge for premium features or additional services, such as advanced analytics and performance reporting. By automating many of the manual steps involved in procurement, Fairmarkit helps its clients cut procurement cycle times by up to 40%, leading to significant cost savings. In summary, Fairmarkit is revolutionizing the way companies manage their tail spend by using machine learning to automate and optimize the procurement process. This allows businesses to save time and money, while also gaining better control over their purchasing activities. Keywords: Tail Spend, Procurement, Machine Learning, Automation, SaaS, Sourcing, Vendor Identification, Cost Savings, Analytics, Subscription Model.

Valuation $100–500M
Revenue $10–50M
Headcount 100–500
Total funding $50–100M
Unlock exact values This page shows ranges. Dealroom has the exact numbers for FairMarkIT and the history behind them.

Investors

14 investors on FairMarkIT's cap table

Sourced from Dealroom's funding history. Investor profile links are shown where available.

Seed 1 investor entered at this stage
Jeavio
Series A 8 investors entered at this stage
1984 Ventures
New Stack Ventures
VT Technology Ventures
MassVentures
Insight Partners
Notable Capital
The New Stack
Newfund
Series B+ 5 investors entered at this stage
Man Capital
OMERS Private Equity
OMERS Growth Equity
Highland Capital Partners
ServiceNow

Global footprint

Where FairMarkIT has talent and traffic

Workforce by country
11 countries with
team presence
🇺🇸 United States56.1%
🇵🇱 Poland26.8%
🇮🇪 Ireland4.9%
🇬🇧 United Kingdom3.3%
🇷🇸 Serbia2.4%
Top 5 of 11 shown
Web traffic by country
120K monthly visits
across markets
🇺🇸 United States29.3%
🇮🇳 India18.4%
🇲🇽 Mexico9.8%
🇪🇬 Egypt7.6%
🇵🇭 Philippines6.1%
Top 5 markets shown

Talent graph

The shape of FairMarkIT's talent

Dealroom maps FairMarkIT's team person by person — pinpointing the standout operators and scoring them across the six dimensions investors underwrite. The counts and shape below are a public preview; the named individuals and exact scores live in the platform.

25 team members profilednamed & role-tagged by Dealroom
148 employeestotal headcount
6 executives & foundersidentified by name
DimensionScore
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Source: Dealroom Talent Intelligence. Public profiles show counts and the team's shape only — request a demo for the named individuals, per-person seniority and tenure, and team benchmarks vs peers.

Market sentiment

What the market is saying about FairMarkIT

An AI-synthesized read of the highest-engagement posts about FairMarkIT on X over the past 7 days. We rank by likes & retweets, ignore corporate channels, and surface the themes that broke out from real people.

Reading the room on X — pulling top posts and synthesizing themes…

Source: X recent search ranked by engagement (likes + retweets) · Synthesis by Claude · Cached for 1 hour

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