quantifAI
quantifAI offers ML Lab, a browser-based machine learning platform that trains classification and regression models entirely client-side, serving privacy-conscious individual data scientists and organizations that need ML without sending data to external servers.
- Company typePrivate
- Founded2021
- Headquarters—
- Headcount1–10
- GTM typeB2C
- OfferingSoftware
What quantifAI does
quantifAI operates ML Lab, a browser-based machine learning platform that enables users to train classification and regression models on their own data without uploading it to any external server. The product executes entirely client-side using WebAssembly and JavaScript on the user's CPU, supporting ingestion of CSV, TSV, TXT, JSON, JSONL, and NDJSON files. ML Lab automatically detects the task type from the target column, trains a small set of standard models (Gradient Boosting, Random Forest, Logistic Regression), holds out a portion of the data for testing, and ranks results against a naive baseline with feature-importance outputs and plots. Constraints include a 10 MB file ceiling, 10,000 rows, 200 columns, and 80 model features — positioning the tool for small to mid-sized tabular datasets rather than production-scale workloads.
The company targets privacy-conscious individual data scientists, ML practitioners, and organizations that cannot transmit sensitive data to third-party cloud services. The architectural choice that data never leaves the device is presented as a verifiable guarantee — users can confirm zero network requests via browser dev tools — rather than a policy promise. This positions ML Lab against cloud ML platforms (e.g., hosted AutoML services) on the dimension of data sovereignty rather than model sophistication.
quantifAI is a private California LLC (QUANTIFAI, LLC) headquartered in Campbell, with 1–10 employees and no disclosed funding, revenue, or pricing model. The product is currently free to use without an account, and the public roadmap signals future features (GPU acceleration, larger datasets, model export, shareable reports) that could broaden the addressable market and potentially enable monetization. No enterprise customers, partnerships, or distribution agreements are disclosed, and go-to-market is product-led via the public website.
quantifAI firmographics
Firmographics- Name
- quantifAI
- Legal name
- QUANTIFAI, LLC
- Website
- https://quantifai.co
- Company type
- Private
- Founded year
- 2021
- Operating status
- Operating
- Headcount range
- 1–10 employees
- Short description
- quantifAI offers ML Lab, a browser-based machine learning platform that trains classification and regression models entirely client-side, serving privacy-conscious individual data scientists and organizations that need ML without sending data to external servers.
- Ownership category
- akta.pro rank
quantifAI industry classification
Industry- Product category
- No-Code Machine Learning Platform
- NAICS
- Computer Systems Design and Related Services (54151)
- SIC
- Services-Computer Programming, Data Processing, Etc. (7370)
- akta.pro primary industry
- AutoML & Low-Code ML Platform Operations (HDAAABAL)
- akta.pro secondary industry
- Model Training & Hyperparameter Optimization (HDAAABAE)
Keywords
quantifAI business model
Business model- GTM type
- B2C
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Marketing or Sales, Operations
Revenue model
- Browser ML Lab (Core Product): The core product is currently offered for free with no disclosed pricing model. Users can run the tool without payment or account creation. The product roadmap mentions future features including model export and shareable reports which may represent paid capabilities.
Go-to-market motion1 record
Distribution channels1 record
Marketing channels2 records
quantifAI product offering
Product offeringCore offering
quantifAI provides ML Lab, a browser-based machine learning platform that lets users train predictive models (classification and regression) on their own tabular data without writing any code or uploading data to a server. All model training, column selection, and file processing run entirely client-side in the user's browser using WebAssembly/JavaScript. The product supports up to 10,000 rows, 200 columns, and 80 model features, automatically detects task type, trains a small set of models, and ranks results against a naive baseline with feature importance and visualizations.
Product overview
quantifAI offers a single unified product called ML Lab, a browser-based machine learning platform. The product runs entirely client-side, allowing users to train classification and regression models on their own data without uploading it to any server. ML Lab handles the full ML workflow including data ingestion (CSV, TSV, TXT, JSON, JSONL, NDJSON), automatic task detection, model training (Gradient Boosting, Random Forest, Logistic Regression), and evaluation against a naive baseline with visual results.
Differentiator
Problem solved
Functional benefit
Brands
- ML Lab: Browser-based machine learning tool that trains models on user data locally without sending data to servers
Quantifiable outcome
- Results delivered in seconds without setup or code
- +1 more outcomes
Companies that use quantifAI
Customer profileSegments2 records
Ideal customer profiles2 records
quantifAI technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- No
- API docs
- API detail
Core technology
AI maturity
App detail
AI capability3 records
Feature6 records
quantifAI partnerships and signals
Strategic signalScale indicators1 record
Recent moves3 records
Expansion highlights4 records
quantifAI competitors and assessment
Company assessmentEmerging players
- RapidMiner: Data science platform with a visual workflow designer and AutoML capabilities, popular with business analysts and academic users. Comparable to quantifAI on the low-code/no-code tabular ML axis, though RapidMiner is a heavier desktop/cloud product.
- H2O.ai: Open-core AutoML and LLM platform with strong enterprise traction and a Driverless AI product. Comparable as an AutoML competitor in the tabular ML space where quantifAI also plays.
Direct peers
- Akkio: No-code AI platform for predictive analytics on tabular data, targeted at marketers and operators without ML expertise. Comparable to quantifAI on the no-code tabular ML axis, though Akkio is a cloud SaaS rather than a browser-local tool.
- Obviously AI: No-code AutoML platform that lets business users upload tabular data and generate predictions in minutes without data science expertise. Directly comparable to quantifAI's target use case of fast, no-code tabular ML for non-technical users.
- BigML: Cloud-based AutoML platform offering a similar model family lineup (boosted trees, random forests, logistic regression) with a comparable no-code interface. Comparable as a no-code ML training tool targeting non-technical users, though BigML is cloud-based rather than browser-local.
- Google Teachable Machine: Google's browser-based, no-code ML tool that lets users train image, audio, and pose classification models without writing code. The closest direct peer to quantifAI on the no-code, in-browser training axis, though Teachable Machine focuses on media classification rather than tabular data.
Broad incumbents
- AWS SageMaker: Amazon's flagship ML platform covering data prep, training, deployment, and MLOps. The dominant cloud ML incumbent; relevant as the reference enterprise buyers compare against when evaluating lighter-weight AutoML tools.
- Microsoft Azure Machine Learning: Microsoft's enterprise ML platform with AutoML, a drag-and-drop designer, and MLOps. Comparable as a broad ML platform incumbent offering low-code/no-code paths that quantifAI implicitly competes with for the same end users.
- DataRobot: Enterprise AutoML and MLOps platform serving Fortune 500 customers across industries. The broader AutoML category incumbent that quantifAI's no-code positioning implicitly competes against, though DataRobot targets a far larger and more technical buyer.
- Google Vertex AI: Google Cloud's end-to-end ML platform with AutoML, custom training, and MLOps capabilities. Represents the incumbent platform risk: a large cloud provider could replicate browser-local no-code ML as a feature within Vertex AI, eroding quantifAI's differentiation.
Market position
Strengths4 records
Weaknesses4 records
Competitive moat5 records
Key risks5 records
Key highlights5 records
Customer concentration
quantifAI social profiles
Digital presencequantifAI financial estimates
Financial estimateRevenue estimate
Valuation estimate
quantifAI leadership team
Management profileNumber of profiles
quantifAI funding detail
Funding detailFunding overview
Funding rounds
Investors
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
quantifAI M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about quantifAI
What does quantifAI do?
quantifAI provides ML Lab, a browser-based machine learning platform that lets users train predictive models (classification and regression) on their own tabular data without writing any code or uploading data to a server. All model training, column selection, and file processing run entirely client-side in the user's browser using WebAssembly/JavaScript. The product supports up to 10,000 rows, 200 columns, and 80 model features, automatically detects task type, trains a small set of models, and ranks results against a naive baseline with feature importance and visualizations.
Is quantifAI a public or private company?
quantifAI is a private company. It is classified as founder individual operated bootstrapped and is currently operating.
When was quantifAI founded?
quantifAI was founded in 2021. It employs 1 to 10 people.
How does quantifAI make money?
One revenue line is on record: browser ML Lab (Core Product).
Who are quantifAI's main competitors?
Emerging players on record are RapidMiner and H2O.ai. Direct peers are Akkio, Obviously AI, BigML and Google Teachable Machine. Broad incumbents are AWS SageMaker, Microsoft Azure Machine Learning, DataRobot and Google Vertex AI.
Does quantifAI have an API?
No public API is recorded for quantifAI.
What industry is quantifAI in?
quantifAI's product category is No-Code Machine Learning Platform. Its primary akta.pro industry code is HDAAABAL, AutoML & Low-Code ML Platform Operations, with a secondary code of HDAAABAE, Model Training & Hyperparameter Optimization. Its NAICS code is 54151 and its SIC code is 7370.