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The data was there.The method wasn't.

No Python. No setup. No clue what a model even is? Fine.
Drop a CSV. Click once. That's genuinely it..

One-time payment · No subscription, ever

Sample output — 180 orders, predicting return likelihood

0.922
Accuracy
0.927
ROC-AUC
0.833
Precision
0.667
F1
Selected model: Logistic Regression · Automatic Comparison Across 4 Models ↓ See full report below

Let's get this out of the way first

Your data doesn't leave
your computer. Ever.

Most AI tools send your data to a server. Insight doesn't. Everything runs locally — on your machine. Turn off the internet. It still works.

No login No API key No data upload Works offline

Other AI tools

  • Data sent to the cloud
  • Processed on their servers
  • Potential for exposure
  • Login required

Insight

  • Runs on your machine only
  • Data goes nowhere
  • Works without internet
  • No login, ever

Honestly. You have the data. The spreadsheet is right there. But then you hit a wall.. "What can I actually do with these numbers?" "Can I predict which customers might leave?" "Is there a pattern here I'm completely missing?" Nobody to ask. No time to learn Python from scratch. Too expensive to outsource every. single. time.


Insight sits right in that gap. The kind of analysis experts run — in a form anyone can actually use.

(It didnt need to be this complicated.)


Analysts who need results fast
If you have a spreadsheet, you're already ready.

People who need insights, not a PhD
You don't need to know what model it picks. You just need the output.

Teams that can't send data outside
Hospitals, legal, finance — data that can't leave the building. It won't.

Researchers who need to present findings
Auto-generated PDF report. Plain-language explanations included.

Anyone tired of "just learn to code"
No Python. No VSCode. No terminal. None of it.

People done with monthly subscriptions
Buy once. Use forever. That's the whole deal.

If you need deep learning, image recognition, LLM-based NLP, or time-series forecasting — there are better tools for that. We'll say so.
For tabular classification and regression — including datasets with text columns — Insight handles it well.

At least one of these will feel weirdly specific to you.

Marketer

"Which customers are actually going to respond to this campaign?"

You've got last campaign's data in a spreadsheet. Upload it. Insight identifies the patterns — who responded, who didn't, and why. The report writes itself.

Operations

"I can feel which customers are about to churn. Can I actually prove it?"

Customer data in Excel is enough. Churn prediction, purchase likelihood, tier classification — stop going on gut feeling. Walk into that meeting with somethign real.

Researcher

"I need to analyze this. But I cannot send it anywhere."

Medical records, survey data, proprietary client info — some things can't go to the cloud. Insight never asks them to. Offline. Completely local. Always.

Team lead

"Outsourcing a simple model costs how much?"

Even basic classification projects can run thousands of dollars. Insight lets you run it yourself. And still no Python.

CS / Support

"We have hundreds of reviews. Reading them one by one isn't working."

Drop the spreadsheet with your review text column. Insight converts it to features and runs classification. Not ChatGPT-level NLP — but good enough to sort positive from negative at scale.


We ran the numbers against the alternatives.

Insight isn't the only way to do AI analysis. But the cost gap is bigger than we expected.

OptionAnnual cost
Outsourcing analysis
$400–$1,200/project, ~2 projects/year
$800–$2,400
Cloud AutoML subscription
$40–$120/month plans
$480–$1,440/year
Learning Python yourself
6–12 months to get to production-ready level
Time cost: unlimited
Insight Pro
One payment, lifetime use
$109
2-year savings At least $800+
One year of cloud AutoML costs enough to buy Insight Pro 4–13 times over.
But Insight is a one-time thing. It works in year one. And year three. And beyond.

Three steps.
We're not being dramatic.

(Seriously.)

01

Upload your file

CSV or Excel. Drag it in. Insight reads the structure and figures out what it's looking at.

02

Pick what you want to predict

"Churn probability." "Purchase likelihood." "Return risk." Click the column you care about.

03

Press the button

Insight handles the rest. Model selection, training, evaluation, prediction. All of it.

04

Read the results. Export if needed.

Not just numbers. Plain-language explanations of what was found and what it means. PDF export included.


Press the button.
This is what comes out.

Sample dataset: 180 online orders → Predicting return likelihood
Includes review text and inquiry text columns — mixed text data works fine, just upload it.

Insight Standard · Analysis Report
Return likelihood prediction
orders_train.csv · 2026-05-17 · Insight 1.0.0
Summary
Task type
classification
Selected model
logreg
Model type
linear
Dataset summary
180
Total rows
0
Excluded rows
180
Training rows
256
Feature columns
Target column  ·  return_yn
Preprocessing
Column Data type Status
order_idcategoricalIncluded
order_datecategoricalIncluded
region / category / payment / source / tiercategoricalIncluded
qty / price / discount / delivery_days / ratingnumericIncluded
review_textcategoricalIncluded
inquiry_textcategoricalIncluded
Model summary
Model Code
logreg
Feature Count
256
Random Seed
42
Performance metrics
Accuracy
0.922
F1
0.667
Precision
0.833
Recall
0.560
ROC-AUC
0.927
Warnings
Auto model selection used — Multiple models evaluated; best performer selected.
High-cardinality categorical column — Some categorical columns have too many unique values.

Insight Standard · actual report sample


Automation

Automatic model selection

No idea which algorithm to use? Good, you don't have to. Insight compares options and picks the best one.

Clarity

Results you can actually read

No raw confusion matrices dumped on you. Model info, performance metrics, warnings — explained in plain language.

Reuse

Save & reapply your model

Built a model that works? Save it. Run new data through it anytime without retraining from scratch.

Setup

Just... open it

No Python installation. No dependencies. One file. Double-click. Works on Windows and macOS.


Getting results is one thing.
Explaining them is another.

Standard gives you predictions. Pro tells you why those predictions came out the way they did — which model was chosen and why, which features drove the outcome, and whether your data has any issues worth knowing about before you trust the results. The difference matters when you're presenting to someone else. "The AI said so" doesn't hold up in a meeting. "Here's the model, here's what it weighted, here's why" does. (That gap is bigger than it sounds.)

Model selection reasoning

Not just "Random Forest selected" — the actual rationale. Non-linearity, overfitting risk, sample size considerations. Shown alongside the result.

Data quality warnings

Class imbalance, missing values, outliers, leakage risk — flags issues in your data before you build on a shaky foundation.

Feature importance

Which columns actually drove the prediction. Useful for explaining outcomes — and for knowing what to fix next.

Advanced PDF report

Data summary · model rationale · key variables · risk flags · result interpretation · recommended next steps. Board-ready, basically.


Insight can't do everything.
Here's exactly what it can't do.

Small datasets produce weak predictions. Bad data in, bad results out. (This is true of every ML tool, not just ours.)

No deep learning. No image recognition. No LLM-based text understanding. No time-series forecasting — "what will next month's revenue be?" isn't in scope. Those need different tools. We'll say so instead of pretending otherwise.

But here’s what it does handle well. Datasets with text columns mixed in. Sentiment classification from review data. Any tabular prediction problem — classification or regression. (It converts text to features and runs the model. Not the same as language understanding — but enough for a lot of real use cases.)

Insight does one thing. Take your spreadsheet data, and make a classification or regression model out of it. Text included. Made as simple as we could get it.


No subscription.
Buy once. Use forever.

We're as tired of monthly charges as you are. Insight is a one-time thing.

Standard

Insight Standard

"Just want to try it" — the right place to start

Lifetime license · one payment, done

💡 Monthly subscription equivalent: ~$5/month — pay once instead

  • CSV / Excel upload
  • Auto column detection & preprocessing
  • Automatic model selection & training
  • Classification & regression
  • Prediction export as CSV
  • Save & reuse your model
  • 기본 Performance metrics
  • Basic metrics & result report
  • Fully local — no internet needed
  • Model selection reasoning
  • Data quality warnings
  • Feature importance
  • Advanced PDF report
Pro · Recommended

Insight Pro

"I need to explain the results" — for real work

Lifetime license · one payment, done

💡 One outsourced project costs more than Insight Pro. Forever.

  • Everything in Standard

Pro only

  • Model selection reasoning
  • Data quality warnings
  • Feature importance analysis
  • Advanced PDF report

Standard is right if

You're just getting started.
You need results fast without the explanation layer.

Pro is right if

Presenting to someone else.
You need to explain why the result came out the way it did.

Both plans run fully local. No internet required. No data leaves your machine.
No login. No API key. 7-day refund, no questions asked.

Do I need to install Python?

Nope. One file, double-click, done. Nothign else to set up.

Does it work on Mac?

Yes. Windows and macOS both supported.

Is my data really staying on my machine?

Turn your wifi off and run it. Still works. That should anwser it.

How much data do I need?

50–100 rows is enough to get started. More data means better results, but you don't need thousands.

What's your refund policy?

7 days, no drama. Send us a quick note about why — we use it to make Insight better, not to gatekeep refunds. Delete the app and we'll sort it out.


If you've read this far,
you probably have data sitting somewhere and no clear next step.

That's exactly who Insight was built for.
No AI consultant needed.
No Python required.
No data leaving your machine.

Just upload the file and press the button.
If it's not for you within 7 days, we'll refund it. Just leave a quick note about why.


Just try it. If it's not working for you within 7 days, full refund.

Leave a quick note about why — we'll use it to make Insight better.

No subscription No login No data exposure

AI tools don't have to feel cold and complicated.
It's software made for people — so we tried to make it feel that way.

We jsut wanted to make it
a little easier, a little clearer.

— namdarine

Built to make things a little easier, a little clearer.