Soleadify

Soleadify is a modern data technology company. We use AI and NLP to capture and refresh web and social media content on over 70 million active SMBs and private companies in 200 countries + 20 languages.

Our technology enables us to convert unstructured content into actionable data that defines what a company does, what products it produces, what technology it uses and what its ESG profile is. We do all of this at high velocity, capturing new businesses and validating all attributes of existing business every week. The speed of our data collection and the frequency of our refresh cycles enable us to monitor material changes to millions of companies.

We deliver via APIs that support two uses: searching and data enrichment. Our APIs are easy and quick to implement, increasing the speed to value creation for our partner and end clients.

Our high quality data supports many use cases including procurement, SMB lending, SMB underwriting and private company market intelligence.

Soleadify is a new generation of B2B data company.

We use AI and NLP to rapidly acquire pedabytes of firmagraphic and technographic data on businesses around the world.

We have particular expertise in SMB data where traditional or legacy data providers are typically weak.
We use several NLP models to break down hundreds of billions of web pages every month and extract usable data with unrivaled coverage, accuracy, and depth.

Like having a data-gathering army at scale.

SMB Underwriting - Quick research and validation of SMBs, identify the insurance codes that make sense for each prospect, and stay up to date with the relevant changes in the business of each client

SMB Lending - Identify early signs of a booming or struggling business and predict churn risk. Gain financial data resources on any SMB and manage risk based on certainty.

Third Party Risk Management - validation of 3rd party entities for risk management and procurement purposes; enrichment of inbound requests to confirm if the entity is valid (active), what industry they fall into, what products they offer, what technology they use, and what ESG footprint they have.

Procurement - Automate supplier screening and mitigate procurement risk – enrich your supplier data with market intelligence to have more understanding of your supplier portfolio.

Data Upkeep - Have company profiles updated every week with new and improved findings. Centralize datasets across your organization through data matching and de-duping.

Market Analysis - Understand the market dynamics that change every week. New companies in each niche, companies going out of business, changes in the market and high-level trends.

Extraction - Soleadify scans the web in a similar way to how humans research companies, and turns unstructured data into rich company profiles.

Curation - Raw information is stored in dedicated big data infrastructures – a combination of ML and algorithms triangulates, deduplicates, and curates the data most likely to be accurate. The result is stored in a database with associated metadata, allowing us to choose which data is returned by which API, based on every usecase’s requirements.

Coverage - Full profiles of the SMBs ignored by everyone else, with unique datasets your competitors don’t have access to.

Accuracy & Granularity - Company Classification relies on what the company communicates about itself – all up to date, accurate, and as granular as needed.

Freshness - The data is updated on a weekly basis from 10M+ data sources – factual data with minimized latency.

Depth - Find all the data that can be found through manual online research - automated and at scale.

Soleadify scrapes publicly available web pages, respecting the robots.txt document of each website.

A series of NLP and AI models are used to extract and structure data from unstructured sources. For example, a company’s main website - especially pages such as “About Us”, “Contact”, “Our Products” - is crawled, as a first step. Machine Learning (ML) models are then used to extract, classify and normalize the data found on these pages. The result of the ML analysis is then stored, used for search, and returned via API.