
Reducto
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Our platform provides a comprehensive toolkit for working with documents the way a human would, combining custom in-house and leading frontier models to power efficient and accurate document workflows.
We are built for enterprise workloads with flexible deployment options from the cloud to fully air-gapped environments, SOC II and HIPAA compliance, and zero data retention.
Reducto is trusted by leading AI teams at companies like Harvey, Scale AI, Toast, Carlyle and Vanta.
Trained on billions of lines of public code, GitHub Copilot puts the knowledge you need at your fingertips, saving you time and helping you stay focused.
Reducto
GitHub CopilotReducto's answer
Reducto is the only agentic document platform that orchestrates custom in-house and frontier models under the hood, automatically routing each page to the right model based on complexity. That means we balance accuracy, latency, and throughput for your specific use case โ not a one-size-fits-all pipeline.
Where others stop at parsing or extraction, we cover the full lifecycle of document work โ parse, classify, split, extract, edit, and workflow orchestration โ in one platform. The result: 99%+ accuracy on the long-tail documents (handwriting, complex tables, scanned PDFs, charts) that break other solutions, with grounded outputs (bounding boxes, citations, confidence scores) so your team can trust what comes out.
Reducto's answer
Performance for you, not for a benchmark. Competitor benchmarks are biased. Reducto encourages head-to-head evaluations on your own documents โ and consistently wins on accuracy, robustness, and the long tail (tables, charts, handwriting, scans). We're not the cheapest; we're the most optimal, automatically balancing accuracy, latency, and throughput for your workload.
Enterprise-ready from day one. Flexible deployment from cloud to hybrid VPC to fully air-gapped, SOC 2 and HIPAA compliance, zero data retention, autoscaling for spiky loads, and white-glove FDE support with custom SLAs. We've processed billions of pages and counting.
One complete platform instead of a stitched-together stack. Parse, Classify, Split, Extract, and Edit endpoints โ plus a Workflows product, agent-ready tooling (CLI, MCP, integrations), and 30+ supported data and file types. Stop maintaining four vendors for one document pipeline.
Reducto's answer
Our primary audience is technical leaders at AI-native companies and document-heavy enterprises โ CTOs, VPs of Engineering, Heads of AI/ML, and Chief AI Officers โ who own AI and platform strategy and are accountable for shipping production AI on messy real-world data. Our champions and end users are the AI engineers, ML engineers, data engineers, and AI platform engineers who actually build on top of Reducto.
We see the strongest fit in regulated, document-heavy industries: financial services, fintech, insurance, healthcare, and legal โ plus the AI-native companies serving them. The common thread: they process large volumes of unstructured documents (often millions of pages a month), they care about accuracy and throughput at production scale, and they have engineering teams that would otherwise burn cycles building and maintaining OCR, parsers, and extraction pipelines themselves.
Reducto's answer
Reducto was founded by Adit Abraham (CEO) and Raunak Chowdhuri (CTO) on a simple observation: modern AI models are exceptional at reasoning, but they're only as good as the data fed into them โ and most real-world data lives in messy, unstructured documents. PDFs, scans, handwritten forms, complex tables, charts. The "odd structure of documents" was breaking otherwise capable AI systems.
So they took a different approach: treat document ingestion as a computer vision problem, not a text problem. By combining traditional CV models with vision-language models in an agentic orchestration layer, Reducto reads documents the way a human would โ interpreting layout, structure, and visual cues before extracting meaning.
What started as a parsing engine has grown into a complete agentic document platform โ powering document workflows for the largest AI teams in the world, with billions of pages processed and counting.
Reducto's answer
It definitely increases my productivity.
Based on our record, GitHub Copilot seems to be a lot more popular than Reducto. While we know about 388 links to GitHub Copilot, we've tracked only 2 mentions of Reducto. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Key to this was software from AI document-management company Reducto, which shared an office building with Kino AI. In another oversubscribed session, developer relations lead Palak Agarwal, explained how the advanced nature of the companyโs code enabled a comprehensive scan of the messy PDF files and organization of the information gleaned into a usable format. - Source: dev.to / about 1 month ago
Yes! We used our friends at Reducto (https://reducto.ai/ to see what I mean. For apps like Jmail and JFlights we use their structured extraction endpoint insteadโyou define a schema (e.g. {from, to, subject, date, body} for emails or {departure_airport, arrival_airport, passengers[], date} for flights) and it pulls those fields directly into JSON. The JFlights example served as the best ad for Reducto and how doc... - Source: Hacker News / 8 months ago
Snagly is a free, MIT-licensed set of 30 skills for AI coding agents โ GitHub Copilot, Claude Code, Cursor, Codex and 70+ others โ that turn "an AI that can drive a browser" into "an AI that tests like a QA professional." A skill, if you haven't met them yet, is a reusable instruction set that teaches the agent a specific working method โ when to use it, what rigor it requires, what evidence to capture, and what... - Source: dev.to / 1 day ago
Where llms.txt genuinely gets read is a different layer: coding and agent tooling โ Cursor, Claude Code, GitHub Copilot, Windsurf โ pulling a documentation site's pages with less token waste, plus emerging agent protocols like OpenAI's Agents SDK. That's real, and it's growing fast. - Source: dev.to / about 1 month ago
You need an active GitHub Copilot subscription. Plans are available at individual, business, and enterprise tiers at github.com/features/copilot. Once active, all tools use your GitHub account credentials. - Source: dev.to / 2 months ago
For over a decade PhpStorm (starting in my WordPress era) and later WebStorm have been my main IDEs for web development. So when GitHub Copilot launched, it was a natural choice to try it out in WebStorm. It was one of the first AI coding tools I used, and it had a big impact on how I thought about AI-assisted coding. - Source: dev.to / 2 months ago
Before we get into it, there are some things about AI usage worth addressing. I've had my fair share of scepticism in the past, but recent model releases have made it increasingly difficult to argue that AI isn't a viable tool for the majority of workstreams, including building user interfaces. Most large language models are trained on public data scraped from the internet, which means your internal design system... - Source: dev.to / 2 months ago
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