We build your IP, your Edge.

Syfter enables private equity firms to accumulate a rich and proprietary data lake, but more importantly it's built to allow machine learning to be applied on that data in a performant and scaleable architecture. The machine learning models we build with our private equity clients are fully owned by them, making the output of Syfter unique to each firm.

Flexible Engagement Models

Our Syfter technology can be accessed in many different ways.

Syfter Platform

We offer a complete package of professional services to build out your own user interface with our UX & UI team - and data science professional services to deliver machine learning models that we build with you. The platform includes out-of-the-box machine learning models for news classification and sector and sub-sector classification and the flexibility to add customisations overtime.

Syfter Backend & APIs

Often our clients will use our technology to integrate new capabilities into existing solutions via our APIs, or build new custom solutions on top of our backend ingestion engine.

Components

Use our individual building blocks to solve challenges you are facing, whether it be licensing our webscraper for a project or using our ingestion engine to further enrich an internal data lake.

The Core Building Blocks

Core features and technology used within Syfter
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Recommendation Engine

At the core of Syfter is a recommendation engine that continuously learns what content and companies are most relevant to you based on your interactions with the product.

Company Modelling

Using content from company websites, Syfter builds a model of each company, extracting keywords and concepts to help the platform get a deep understanding of each company. It also classifies the company into a sector.

Company Matching

Using the company models, Syfter is able to match company mentions within third-party sources. It does this via fuzzy matching and by analysing terminology used within an article and how related it is to the target company.

News Signal Classification

Using natural language processing, Syfter is able to understand the subject of a news article and extracts signals such as board changes, acquisitions, product launches, and much more

News and Blog Extraction

Alongside extracting concepts and keywords, Syfter detects news articles, blog posts and press releases that have been published on company websites and continuously ingests them into your campaign.

News Summarization

Syfter allows you to quickly understand the content of an article via auto-generated summaries. Summaries are displayed against each recommended article within the platform and also used in your daily snapshot emails.

Daily Emails

Syfter allows you to issue a daily summary email to showcase the highlights of a campaign output in the previous 24 hours. This can be configured to a range of users across the company.

Ingestion Engine

Syfter includes a flexible, highly scalable, ingestion engine that allows us to easily ingest content from both internal and external data sources.

Our Roadmap

Syfter is continuously improving with new data connectors, refined machine learning models and new core features.

Syfter is comprised of a number of technologies that solve the challenges that private equity firms face around discovering and monitoring private companies at scale.

Book a free walkthrough to see how the Syfter platform could work for you.

Syfter AI – Automating Deal Origination for Private Equity Firms
 
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