Shofo

Problem/Solution Report

Problem – Social media contains the largest repository of human behavioural signals, yet access is fragmented, incomplete, and often stale. Practitioners face “partial snapshots,” “stale dumps,” and platform‑specific barriers that require months of engineering to turn unstructured content into model‑ready datasets. Traditional scraping demands proxy management, anti‑bot evasion, and brittle code maintenance.

Solution – Shofo builds and maintains continuous, live indexes across major platforms (TikTok, Instagram, X, LinkedIn). The product exposes a SQL‑ready interface and per‑record API endpoints, delivering hundreds of millions of posts, profiles, and interactions in real time. Pricing is transparent and usage‑based (e.g., $0.0001 per record, with optional transcript and video add‑ons).

Value Proposition – By providing live indexes with 200+ fields per TikTok video, Shofo eliminates the need for teams to build bespoke scrapers and labeling pipelines. Customers can run granular queries (e.g., “Which beauty videos from Brazil received the most comments in Q4 2025?”) and pay only for the data they retrieve, accelerating AI model training, content analytics, market research, and prediction‑market workflows.

Differentiation – Compared to DIY scraping or generic scraping APIs, Shofo offers a maintained, multi‑platform, structured dataset with real‑time freshness and per‑record pricing. Backed by Y Combinator and led by a team with ML research (MIT MSRP), cloud infrastructure (AWS) and prior startup experience, Shofo is positioned to deliver reliable, compliant, and high‑quality social data at scale.

Market and Competitors Report

Market Context – Real‑time social data demand is rising alongside AI and analytics adoption. Grand View Research projects the global Social Media Analytics market to grow from USD 10.23 billion in 2024 to USD 43.25 billion by 2030 (CAGR 27.2%). Data‑as‑a‑Service and AI training dataset markets also show strong double‑digit growth, supporting Shofo’s multi‑segment opportunity.

Competitor Landscape

• SocialData.tools – X/Twitter‑focused API offering pay‑as‑you‑go pricing ($0.20 per 1,000 tweets). Lacks multi‑platform coverage and the rich, indexed schema Shofo provides.
• Apify (TikTok Scraper Actor) – Low‑code scraping platform that extracts TikTok data with a pay‑per‑event model. Requires customers to build and maintain their own pipelines.
• Zyte API – General web‑scraping API with headless browsing and AI extraction. Flexible but not a pre‑built, continuously updated social‑media index.

Positioning & Advantages – Shofo’s live, multi‑platform indexes with SQL‑ready access and per‑record pricing reduce integration friction compared to generic scraping APIs or one‑off actors. High field counts (200+ per TikTok video) and optional enrichments (transcripts, video files) enable direct feeding of data into ML pipelines.

Target Users – AI labs, academic/commercial researchers, marketing and analytics teams, and quantitative/ prediction‑market builders who need fresh, structured social data without building scrapers.

Risks – Platform policy changes, compliance (GDPR/CCPA), and anti‑bot defenses could affect data availability. However, the overall market momentum toward real‑time analytics and AI data needs, combined with Shofo’s compliance‑focused design, positions it competitively.

Founders and Background Report

Shofo was founded in 2025 and is a Winter 2026 Y Combinator company building large‑scale, continuously updated indexes of social media content for AI training and analytics. The founding team comprises four co‑founders:

• Bryan Hong – CEO – Listed on Y Combinator as a Berkeley dropout. A LinkedIn post describes how he and his co‑founders shut down a prior startup (Correkt) and moved to San Francisco to build Shofo’s live social media indexes.
• André Braga – Head of AI – Holds a B.S. in Statistics & Data Science from UCSB and was a 2025 MIT MSRP intern working on reinforcement learning for trustworthy LLMs. The MIT profile confirms his role in designing Shofo’s fine‑tuning workflows and ML infrastructure.
• Braiden Dishman – COO – Holds a B.A. in Economics from UCSB and previously worked at AWS. The YC profile lists him as part of the core team that pivoted to continuous social‑media indexing.
• Alexzendor Misra – CTO – A UCSB dropout who previously served as CEO of Correkt (43k users). The YC and LinkedIn sources note his technical leadership in building the indexing platform.

The team’s combined background in ML research, cloud infrastructure, and prior startup experience underscores strong founder‑market fit for a data‑intensive AI tooling company.