Data collection as a service
You have an idea that runs on data: a model to train, a product to launch, research to publish, a market to understand. The hard part is getting the data. It is scattered across websites, locked inside PDFs and scans, sitting in public portals nobody has time to wrangle, or it does not exist in usable form yet.
We source it the right way, by whatever method fits, then clean, structure, and validate it so you get a dataset you can build on from day one. Every engagement starts with a free feasibility check on your sources, so you see what is possible before you commit.
Get a free feasibility check →Most projects stall because the data spans half a dozen places, each with its own format, access rules, and quirks. We work across all of them and hand you one clean dataset.
Government and institutional datasets (data.gov.in, the Reserve Bank, the Ministry of Statistics, sector portals), pulled, reconciled, and made analysis-ready.
Clean it at scale →Catalogues, prices, listings, directories, and reviews extracted reliably across thousands of pages, including sites that fight back.
See web scraping →Invoices, ledgers, forms, registers, and images turned into structured rows and fields, including handwriting and regional formats.
See data digitization →Catalogue, price, and availability feeds across quick-commerce and marketplace apps, refreshed on the cadence you need.
See quick commerce data →When a paid or partner application programming interface is the cleanest route, we integrate it, handle the limits and authentication, and fold it into the same dataset.
When the data does not exist yet, we create it: surveys and panels, structured field and store-level capture, and expert tagging and labelling.
No black box. You see the plan and a sample before any build, and you know exactly how the data was put together.
We deliver in the format your stack expects, validated and documented, so your next step is building, not cleaning. And because we are an end-to-end data company, we can take it further whenever you want.
A labelled, balanced dataset ready for feature engineering and training, not a raw dump you spend weeks cleaning first.
Feed demand forecasts, churn scores, and anomaly detection with data that is fresh, matched, and trustworthy.
Structured data wired straight into your business intelligence tool, so a chart reflects reality instead of guesswork.
Drop the collected dataset into our ask-your-data layer and query it in plain language, no SQL required.
We can host the collected dataset as an authenticated, auto-refreshing API endpoint, the way our quick commerce data API already serves live catalog and pricing feeds. Your product or partners query it directly and always get current data.
We pick the source and method that actually fit your problem, not the one we happen to sell. Often it is a mix.
A free check on your sources, with a sample and a legality read, before you commit a rupee. You see the quality up front.
Collection is the start. We can take the same dataset into clean pipelines, forecasts, and dashboards whenever you are ready.
Built and scoped for Indian SME budgets, with clear deliverables instead of a vague enterprise quote.
For public data, generally yes, but the details matter and we scope them with you before we start. India has no statute that specifically bans collecting public data. The Digital Personal Data Protection Act 2023 does not apply to personal data that a person has made publicly available (Section 3(c)(ii)), which covers most public web and open data.
Accessing a system without authorization can fall under Section 43 of the Information Technology Act 2000, and a source's terms of service can create contractual limits. So we focus on public, permitted data, respect robots and rate limits, avoid personal or sensitive data unless you have a lawful basis, and flag anything that needs your legal sign-off.
This is general information, not legal advice.
Everything you need to know about the service and how it works. Can’t find an answer? Mail us at info@galific.com
