datavyn turns messy web and business data into structured datasets, forecasts, and dashboards you can act on. Pick from 200+ ready-made scrapers, or bring a problem and get a custom-built solution.
From first extraction to final dashboard — every step of the data journey, handled.
Exploratory analysis that uncovers the trends, patterns, and opportunities hiding in your data — so decisions rest on evidence, not guesswork. You get clear findings, not a wall of numbers.
Predictive models built on your historical data to estimate demand, prices, and behavior before they happen. Plan inventory, budgets, and campaigns with a view of what's coming.
Statistical and machine-learning techniques for the harder questions — segmentation, prediction, and anomaly detection that simple reporting can't answer.
Interactive dashboards and clean reports that turn complex datasets into something your whole team can read at a glance — and keep current as new data arrives.
The habits that make client work land: clean data, clear communication, and tools that already exist when you need them.
Every deliverable arrives analysis-ready: consistent fields, deduplicated rows, CSV, JSON, or Excel — straight into your sheet, database, or BI tool.
200+ scrapers already built for e-commerce, real estate, social, jobs, and leads — and custom builds when your target isn't in the library.
Existing tools run today; custom scrapers and analyses ship in days, not months. Small, focused projects are the specialty.
Python, pandas, machine learning, and battle-tested scraping stacks (httpx, curl_cffi, BeautifulSoup) — the same tools behind every project.
Based in Lahore, working across time zones with clients everywhere. Clear written updates, no meetings required.
Honest scoping before any commitment: what's feasible, what it costs, and what the data can and cannot tell you.
A simple, predictable path — whether it's one scraper or a full analysis pipeline.
Email what you're trying to learn or collect — a site to scrape, a forecast you need, a dataset that confuses you.
You receive a plain-English plan: what's feasible, the approach, timeline, and a fixed quote. No surprises later.
Scrapers run, models train, dashboards take shape — with progress updates and samples along the way.
Clean files, working tools, or live dashboards land in your hands, documented and ready to plug into your workflow.
E-commerce, real estate, social media, jobs, leads, finance, travel — plus free utilities. Every tool documented on its own page.
Browse the scraper library →A sample of the analysis and machine-learning work behind datavyn.
Trained a neural network to steer a simulated car from camera input — an end-to-end deep-learning pipeline from data collection to a model driving the track.
Healthcare AnalyticsExplored clinical records to identify which patient characteristics correlate with mortality risk, turning raw hospital data into interpretable risk factors.
Data AnalysisAnalyzed accident records to surface the conditions and locations where crashes cluster — evidence a safety program can act on.
Predictive ModelingBuilt models on live London accident data to predict severity and link outcomes to weather conditions as they change.
Two things that work together: a library of 200+ ready-to-use web scrapers and data tools, and custom data-science services — exploratory analysis, forecasting, advanced machine-learning analysis, and interactive reports and dashboards. You can use a ready-made tool as-is, or bring a problem and have the whole pipeline built for you.
The library contains tools that already exist — each page describes what the tool collects and returns, and they're the fastest, most economical option. Custom projects are scoped from scratch: a scraper for a site not in the library, a forecast built on your data, or a dashboard for your team. Custom work is quoted per project after a short scoping conversation.
The tools collect publicly available data only — nothing behind logins or paywalls. That said, how you use collected data is your responsibility: you should comply with target websites' terms of service and applicable laws (including copyright and data-protection rules like GDPR/CCPA where they apply). If a use case looks problematic, you'll be told before work starts.
Usually, yes. Most public websites can be scraped with the right approach, and custom builds are a core part of the practice. A few heavily protected sites are impractical to do reliably — you'll get an honest feasibility answer before committing, not after.
Whatever fits your workflow: CSV, JSON, or Excel for datasets; runnable Python tools where useful; and interactive dashboards or written reports for analysis work. Output is always clean and structured — consistent fields, deduplicated rows, ready for a spreadsheet, database, or BI tool.
Ready-made tools can run the same day. Small custom scrapers typically ship within days; larger analysis, forecasting, or dashboard projects take longer and get a timeline in the quote. To start, email jamshaid@datavyn.com or use the contact form with a couple of sentences about what you need.
Full analysis is half the practice. Beyond extraction, datavyn covers data cleaning, exploratory insight work, forecasting, machine-learning techniques like segmentation and anomaly detection, and dashboards — the portfolio includes healthcare analytics, traffic-safety studies, and predictive modeling projects, not just scrapers.
Project-based and agreed up front. After you describe what you need, you get a plain-English scope with a fixed quote — no hourly meters, no surprise invoices. Small tool runs cost little; bigger pipelines are priced by the work involved. Reach out for a quote on your specific case.
datavyn is the data practice of Jamshaid Arif — a data scientist who has been extracting, cleaning, and modeling web data since 2020. What started as web scraping grew through data analysis into machine-learning engineering, and datavyn now covers the full journey: getting the data, understanding it, predicting with it, and presenting it so people actually use it.
The work splits into two halves that feed each other. The first is the scraper library — more than 200 ready-to-use tools that pull structured data from e-commerce sites, real-estate portals, social platforms, job boards, business directories, and public data sources. Each tool has its own page describing exactly what it collects and returns, and every one delivers clean, deduplicated output in CSV or JSON. If a source you need isn't covered, a custom scraper is usually a short project away.
Collecting data is only the start. Most clients come with a question, not a URL: What will demand look like next quarter? Which listings are underpriced? Why did this metric move? Answering those takes the second half of the practice — exploratory analysis that finds the story in the data, forecasting models that project it forward, advanced techniques like segmentation and anomaly detection when the question is subtle, and dashboards that keep the answer alive as new data flows in. The toolkit is Python end to end: pandas for wrangling, scikit-learn-style modeling for prediction, and modern scraping stacks like httpx, curl_cffi, and BeautifulSoup for extraction that holds up on real-world sites.
datavyn works best with founders, analysts, marketers, and researchers who need data work done properly but don't need a full-time data team. Typical engagements include price and competitor monitoring for e-commerce sellers, lead lists built from business directories, property-market datasets for investors, research datasets for academics, and forecasting or dashboard projects for small businesses that have data but no one to make sense of it. Projects are scoped in plain English with a fixed quote before any work begins, and deliverables arrive documented — files, code, or dashboards you can keep using without me.
Two principles run through everything. First, the tools collect publicly available data only, and clients are responsible for using data lawfully — that's stated up front rather than discovered later. Second, no overpromising: scraping depends on what target sites expose, models are only as good as the history behind them, and a straight "that won't work, here's what will" is part of the service.
Every custom engagement sharpens the library, and the library accelerates every engagement. When a client needs competitor prices, an existing e-commerce scraper gets the first cut of data on day one while the custom pieces are built around it. When a new source gets scraped for a project, it often becomes a documented tool others can use later. That loop is why turnaround stays short without cutting corners: most of the plumbing already exists, tested against real websites, so project time goes into the part that is genuinely new — your question, your data, your decision. It also means estimates come from experience rather than optimism, because close variants of most requests have been built before.
If you have a dataset that needs sense made of it, a website that needs turning into a spreadsheet, or a decision that needs numbers behind it, send a short note about what you're trying to do. You'll get a clear answer about feasibility, timeline, and cost — usually within two business days.
Describe what you need — a scraper, a forecast, a dashboard, or just help understanding your data — and get a plain-English answer on feasibility and cost.
Or email directly: jamshaid@datavyn.com
Based in Lahore, Pakistan — working with clients worldwide. Typical reply within 1–2 business days.