Launching today
OrangeLabs
Analyze, interpret, and create interactive visuals from data
192 followers
Analyze, interpret, and create interactive visuals from data
192 followers
OrangeLabs helps teams to analyze, interpret, and communicate complex data using AI. Upload/connect data, ask questions, and instantly get tables, charts, and insights. No formulas or code needed. Founders, analysts, and data teams use OrangeLabs AI agent to turn raw spreadsheets into clear decisions in seconds. Get started for free at: orangelabs.im
Interactive
Free Options
Launch Team / Built With
Hey Product Hunters! ✌️✌️✌️
I’m Manish, founder at Orangelabs.im, with my co-founder @neelanchal_gogna.
We’re beyond excited to share the OrangeLabs with the world.
💡 What is OrangeLabs?
OrangeLabs is the only no-code platform that empowers anyone to communicate with complex data.
From complex data - to analysis, visual creation, and insights using AI - without writing a single line of code (unless you want to 😉)
Ask:
💬 “Handle missing values or duplicates in the spreadsheet.”
💬 “Build a bar graph stating - which sectors had a sudden drop in user engagement?"
💬 “Highlight the data summary from the attached PDF.”
…and get accurate visual insights with interactive charts and previews.
- no dashboards to learn, no manual reports to build.
🎯 Who is it for?
• Entrepreneurs & Business Owners - Make data-driven decisions without a data team.
• Analysts - Turn complex datasets into interactive visuals and insights without SQL and Python scripts.
• Researchers - no-code trend analysis.
• Anyone with Data - create compelling, easy-to-understand infographics for public consumption.
The only thing that they need to do is "Just Ask."
💡 Why did we build OrangeLabs?
We started as data professionals, but every month, switching between spreadsheets, tools, and dashboards, just to answer simple questions:
“What’s the trend?”
"How did revenue change after we increased rates?"
"How to audit spreadsheets for anomalies?"
That pain was bigger than anything we’d felt before.
So we built Orangelabs for our fellow founders and teams who want a PhD-level data expert (OrangeLabs) constantly working at their side 24*7*365.
Key Highlights
✅ Build interactive data visuals
✅ Process messy data into clean and structured data
✅ check progress with real-time preview
✅ Conversational AI interface - just ask in plain English
Curious about interactive data visuals?
😀 Try it out for free: orangelabs.im
Follow us on X: https://x.com/Neelanchalgogna
https://x.com/orangelabsim
https://x.com/mk_bharat07
Follow us on LinkedIn:
https://www.linkedin.com/in/-mk-/
https://www.linkedin.com/in/neelanchalgogna/
https://www.linkedin.com/company/orangelabsim
💬 We’d love your feedback! And if you need any help, reach out anytime - hi@orangelabs.im
We’ll be around all day to answer any questions.
Zivy
Congrats on the launch, @mk_orangelabs and @neelanchal_gogna!
I loved the vision of making data analysis as simple as “just ask” , especially for founders and teams who don’t want to jump between dashboards, SQL, and spreadsheets.
Curious: how does OrangeLabs ensure accuracy and reliability of insights when users ask open-ended questions on messy or multi-source datasets? Would love to learn more about how you handle that. 👀
OrangeLabs
@harkirat_singh3777 Thanks for your support. And great question, one that most of our users might want to know the answer to.
The answer to this is, before any analysis even begins, OrangeLabs runs an automatic data profiling step (we have a separate layer for it), it detects missing values, duplicates, inconsistent formats, and schema mismatches across sources. So the data is cleaned and structured before insights are generated, not after.
For open-ended questions, our AI agent breaks the query into smaller, verifiable steps rather than attempting one large inference leap.
That said, we're not going to pretend it's perfect. Messy, multi-source data is genuinely hard, and we're continuously improving how we handle edge cases. Feedback from users is exactly how we'll get better.
The "no formulas, no code" positioning is smart because honestly that's the part that kills momentum for most teams. You have the data, you know what question you want answered, but then you spend an hour fighting pivot tables or writing SQL queries.
Interactive charts is the key feature imo. Static screenshots of graphs that get stale in a day is what most people are dealing with. How does the AI handle messy data though? Like CSVs with inconsistent formatting or missing columns?
@mihir_kanzariya
OrangeLabs handles messy CSVs really well. You just upload the file and tell it what's wrong, or even let it detect issues on its own.
For example, you can say:
"Find and fix missing values in this file."
"Standardise inconsistent date formats across columns"
"Flag rows with empty or null entries"
It understands the structure of your data, identifies the inconsistencies, and cleans it, with a real-time preview so you can see exactly what changed before committing.
Missing columns, duplicate rows, formatting mismatches- it handles it.
Would love for you to try it and break it with your messiest file 😄, that's genuinely how we get better.
minimalist phone: creating folders
Can be data exported to Figma where the user can polish the design a bit?
OrangeLabs
@busmark_w_nika Great question! Figma export is actually on our roadmap, the ability to push your charts and visuals directly into Figma, so you can polish the design to your liking.
We haven't shipped it yet, but it's something our team is actively working on. Stay tuned for our next launch, we'd love for you to be one of the first users to try it when it's live!
minimalist phone: creating folders
@neelanchal_gogna Happy to see that it is your priority too :)
@edgeghost
Exactly, that assumption is the whole problem we're solving.
Real-world data is never clean.
We built @OrangeLabs specifically for that reality, not the perfect CSVs that exist in tutorials.
Inconsistent column naming?
Just tell it: "These three columns are all referring to the same thing- merge them."
Mixed formats in the same column?
Just tell it: "Standardise all date formats in this column to DD/MM/YYYY"
It reads the actual structure of your file first, understands the inconsistencies in context, and then acts on your instruction, with a live preview before anything is finalised.
The goal was simple: if one can describe the problem, @OrangeLabs should be able to fix it. No prior data knowledge or technical expertise needed.
Tried with a marketing sheet and asked it to clean up rows with no email IDs. Worked for me. Can be useful. Good Work
OrangeLabs
@aryan_rajput8 That can also be a way of using it.
Hey guys, congratulations on the launch!
How well does it handle really large datasets or multiple connected data sources?
OrangeLabs
@ignacio_borrell @OrangeLabs Syncs directly with existing data sources. We don't plan on hoarding user data. Rather act as an analytic layer between the data layer and the end user.
You can connect multiple data sources at one go. You won't face any issues with it.