Building great AI isn t just about algorithms it s about the data behind them.
That s where Forage AI comes in.

Our new Data-for-AI solution helps teams access clean, structured, and high-quality datasets for training, fine-tuning, and evaluating AI models at scale.

Whether you re developing LLMs, RAG systems, or domain-specific AI agents, we make it easier to source the data you actually need not just what s available online.

What makes it different

Money is not everything, but it can be a means to generate happiness. I am just honest. :D

What steps / financial decisions changed your life for the better in the long run?

Last week, OpenAI announced a full-year free subscription for Indian users starting November 4.
On top of that, they ve rolled out a Learning Accelerator program offering 5 lakh ChatGPT licenses to students and educators, and begun hiring engineers in Bengaluru.

So why the sudden focus?

Here s my take:

• India is now OpenAI s 2nd-largest user base, and probably the fastest-growing.

• By locking in early brand trust and language familiarity, OpenAI is essentially building a moat for the next billion users.

• The country has 700 million + internet users, but very low per-capita SaaS/AI spending. That s a huge conversion opportunity.

• Local competition is heating up as Perplexity, Gemini, and even smaller Indian startups are fighting for daily-use adoption.

For years, SaaS pricing revolved around seats.

If you're adding more teammates then pay more.

This was simple, predictable and scalable.

Currently reading about the move of California:

The state has become the first U.S. state to regulate AI companion chatbots. Governor Gavin Newsom signed SB 243, a new law requiring companies like OpenAI, Meta, Character AI, and Replika to implement safety protocols protecting children and vulnerable users.

For enterprises needing comprehensive data extraction:

• Forage AI Fully managed IDP services processing millions of documents with over 99% accuracy, built for large-scale custom enterprise projects

• UiPath IXP Platform solution integrated with RPA ecosystem, 93% accuracy

• ABBYY Vantage Low-code/no-code platform with pre-built models with strong OCR capabilities

• Microsoft Azure AI Cloud-native API, trains models with samples, Azure ecosystem integration

• Hyperscience Up to 99% accuracy through a proprietary model architecture called Hypercell

• AWS IDP Developer APIs using Textract/Comprehend, require technical orchestration

• Google Document AI Cloud API with template-free GenAI extraction, minimal training needed

• Rossum Template-free approach using LLM for transactional documents

• Docsumo SMB-focused template-based solution with over 95% accuracy

• Docparser No-code tool with point-and-click setup, basic OCR for simple documents

Choosing an Intelligent Document Processing solution shapes your data collection strategy for years ahead.

Unlike APIs, which only provide the data that marketplaces choose to share, custom e-commerce scrapers dynamically collect product details directly from website pages. Modern AI-powered scrapers significantly improve upon outdated methods that often fail due to website updates, ensuring a continuous data flow without the need for constant manual intervention.

Modern AI-powered systems can:

• Parse unstructured website content in real time.

• Adapt automatically when website layouts or anti-bot defenses change.

• Normalize diverse product information into highly structured e-commerce datasets.

• Apply Natural Language Processing (NLP) to analyze reviews and customer sentiment.

I ve spent years working with teams who needed structured data, but 80% of the time went into data scraping, cleaning, or fixing pipelines.
Forage AI solves that it lets you focus on what the data means, not how to get it.
Whether you're enriching leads, tracking news, or feeding LLMs we re here to help.
Excited to learn how the community uses it and where we can do better.