Complete property intelligence from every major listing portal prices, listings, agent data, and market trends.
The real estate market is fragmented, local, and data rich. Thousands of properties are listed daily across portals like 99acres, Magicbricks, Housing.com, and Nobroker. Each listing contains property type, size, price, location, amenities, floor plan, age of construction, furnishing status, and developer details. This data changes constantly as properties are listed, price reduced, marked sold, or taken off market. We help real estate investors, developers, brokers, and proptech companies collect and structure this publicly available listing data at scale. Our extracted intelligence supports property valuation, market trend analysis, competitor benchmarking, and lead generation.
Our real estate data solutions cover residential and commercial properties across multiple cities and micro markets. We extract listing details including property type such as apartment, villa, plot, or office space. We capture pricing data like asking price, price per square foot, negotiability flags, and price change history. We collect property attributes including bedroom count, bathroom count, carpet area, super built up area, balcony presence, parking availability, floor number, and total floors. We also extract location intelligence such as neighborhood, landmark proximity, connectivity scores, and nearby amenities like schools, hospitals, and metro stations. For example, we can extract all 3 BHK apartment listings in a specific zip code, calculate the average price per square foot, and identify which developers command a premium. We can detect that listing volumes in a neighborhood have dropped 30 percent month over month, signaling a supply squeeze. We can also track how long properties stay on market before price reductions, revealing buyer demand levels.
We build custom real estate extraction pipelines based on your target cities, property types, price bands, data fields, and extraction frequency from daily to weekly. Delivery options include property dashboards, price trend reports, inventory heatmaps, developer performance scorecards, and API feeds into your valuation or market intelligence systems. With our data, real estate investors identify underpriced properties and emerging micro markets. Developers benchmark their projects against competitor offerings. Brokers generate qualified leads from fresh listings. And proptech platforms power their valuation models with accurate, current market data.
Property listings are the lifeblood of real estate markets. Thousands of new listings appear daily across portals like 99acres, Magicbricks, Housing.com, and Nobroker. Each listing contains structured and unstructured data about the property, its location, the seller or broker, and the asking terms. Manually collecting this data across multiple cities and property types is impossible at scale. We help real estate investors, developers, brokers, and proptech companies extract listing data automatically and frequently. Our extracted intelligence powers property valuation, lead generation, market analysis, and competitor tracking.
Our property listing extraction solutions capture all major data fields from residential and commercial listings. We extract basic property details including listing title, description, property type such as apartment, villa, plot, or office, listing status like available, sold, or rented, and listing date. We capture pricing data including asking price, price per square foot, negotiability indicator, and any price change history. We extract property specifications such as number of bedrooms and bathrooms, carpet area, super built up area, total floor, floor number, age of construction, furnishing status including unfurnished, semi furnished, or fully furnished, and parking availability. We also extract location details like full address, locality, city, pin code, landmark proximity, and connectivity information. For example, we can extract all 2 BHK apartment listings in a specific pin code with prices, sizes, and furnishing status, then calculate the median price per square foot for comparison. We can detect new listings posted within the last 24 hours in a target neighborhood for lead generation. We can also track how listing descriptions emphasize different features such as "near metro" or "gated community" across different localities.
We build custom listing extraction pipelines based on your target cities, property types, price ranges, data fields, and extraction frequency from hourly to weekly. Delivery options include property listing dashboards, new listing alerts, market inventory reports, and API feeds into your CRM, valuation engine, or market intelligence platform. With our data, real estate investors find underpriced properties faster than competitors. Brokers generate leads from fresh listings instantly. Developers benchmark their project listings against nearby competing properties. And proptech platforms keep their property databases current without manual entry.
Property valuation is not static. Prices change by season, by locality, by project age, and by market sentiment. A property listed today at a certain price may be overpriced or underpriced depending on recent trends in its micro market. Without systematic price data, investors overpay, sellers underprice, and brokers lose credibility. We help real estate businesses extract and analyze pricing data from property listings over time. This includes current asking prices, historical listing prices, price change events, and derived metrics like price per square foot. Our extracted intelligence enables accurate valuations, investment decisions, and negotiation strategies.
Our price trend and valuation intelligence solutions extract listing price at the time of posting and track every subsequent price change. We calculate price per square foot using extracted carpet area or super built up area. We aggregate pricing data by locality, property type, bedroom count, and age bracket to generate market benchmarks. We also identify price reduction frequency and magnitude to detect motivated sellers. For example, we can extract 12 months of historical pricing data for 3 BHK apartments in a specific neighborhood, plot the trend line, and identify whether current asking prices are above or below the rolling average. We can detect that a particular project has seen five price reductions on the same unit over six months, indicating a highly motivated seller. We can also benchmark a developer's new launch pricing against completed projects in the same micro market to assess whether the premium is justified.
We build custom price trend pipelines based on your target cities, localities, property types, bedroom configurations, historical depth, and extraction frequency from daily to weekly. Delivery options include price trend dashboards, per square foot heatmaps, valuation benchmark reports, motivated seller alerts, and API feeds into your valuation engine or investment analysis tools. With our data, investors identify markets with upward momentum before prices rise further. Sellers set realistic asking prices based on comparable data. Banks and appraisers validate property valuations with independent market evidence. And proptech platforms power automated valuation models with fresh, accurate pricing data.
Not all properties are created equal. Two apartments in the same building with the same size and floor plan can have different asking prices based entirely on amenities. One has a balcony. The other does not. One includes covered parking. The other offers only open parking. One complex has a swimming pool and gym. The other has none. These features directly impact buyer preference and price per square foot. We help real estate businesses extract amenity data from property listings at scale. Our web extraction pipelines capture structured and unstructured amenity information from portals like 99acres and Magicbricks. The extracted data can then be used for feature gap analysis, premium calculation, and competitor benchmarking.
Our amenity and feature extraction solutions pull data from listing descriptions, specification tables, and bullet point feature lists. We extract parking related features including covered parking, open parking, visitor parking, and electric vehicle charging. We capture recreational amenities such as swimming pool, gym, clubhouse, children's play area, tennis court, jogging track, and yoga deck. We extract convenience and lifestyle features like balcony, servant room, study room, store room, and pooja room. We also extract safety and infrastructure amenities including 24x7 security, CCTV, intercom, fire safety systems, power backup, lift, rainwater harvesting, and sewage treatment plant. For example, we can extract amenity data from 500 apartment listings in a specific locality to identify which features are most commonly offered and which are rare. We can extract covered parking availability across competing projects to see how your offering compares. We can also extract amenity lists from new project launches to track what competitors are including as standard versus premium upgrades.
We build custom amenity extraction pipelines based on your target cities, property types, amenity categories, and extraction frequency from weekly to monthly. Delivery options include extracted amenity datasets in CSV or JSON formats, structured feature matrices, automated reports highlighting amenity patterns, and API feeds for integration into your internal analysis tools. With our extracted data, developers identify amenity gaps in competitor projects. Investors compare feature packages across shortlisted properties. Marketing teams access accurate amenity data for campaign messaging. And analysts perform their own pricing models using clean, structured extraction outputs.
The rental market moves differently than the sales market. Rental listings change weekly. Deposit amounts vary by locality and property type. Furnished versus unfurnished status can double the monthly rent. Lease terms range from six months to three years. Without systematic extraction of rental data, landlords underprice units, tenants overpay, and property managers miss market shifts. We help real estate businesses extract rental listing data from portals like 99acres, Magicbricks, Housing.com, and Nobroker at scale. Our web extraction pipelines capture rental specific data fields including monthly rent, security deposit, maintenance charges, lease duration, furnishing level, and tenant preferences like family or bachelor friendly.
Our rental market extraction solutions pull structured data from rental listing pages. We extract basic rental details including monthly rent, negotiability indicator, rental availability date, and listing age. We capture deposit and fee information such as security deposit amount, brokerage fee, maintenance charges, and utility inclusions like water or electricity. We extract lease terms including minimum lease duration, maximum lease duration, lock in period, and notice period requirements. We also capture tenant preference data including family friendly, bachelor friendly, pet friendly, and gender preferences for shared accommodations. For example, we can extract monthly rent data for 2 BHK apartments across five localities, compare averages, and identify which neighborhoods offer the best rental yields. We can extract security deposit requirements as a multiple of monthly rent to see which landlords demand higher upfront payments. We can also extract furnished versus unfurnished rental prices to calculate the premium for fully furnished units in a specific micro market.
We build custom rental extraction pipelines based on your target cities, localities, property types, rental budget ranges, and extraction frequency from daily to weekly. Delivery options include rental listing datasets, monthly rent heatmaps by locality, deposit benchmark reports, lease term summaries, and API feeds into your property management or investment analysis systems. With our extracted data, property managers set competitive rents based on actual market listings. Real estate investors identify high yield rental markets. Tenants and relocation companies access current rental data without manual searching. And analysts track rental inflation trends using clean, historical extraction outputs.
Commercial real estate operates differently than residential. Leases are longer. Pricing models vary between monthly rent and price per square foot per annum. Property attributes include floor plates, ceiling height, power backup, loading docks, and business park amenities. The clients are businesses, not families. We help commercial real estate brokers, investors, facility managers, and proptech companies extract commercial listing data from any online source. Our web extraction pipelines are platform agnostic. We can target local classifieds, national portals, regional platforms, and global real estate marketplaces across any country or language.
Our commercial real estate extraction solutions pull data for multiple property types including office space, retail shops, showrooms, warehouses, industrial sheds, coworking spaces, and business parks. We extract pricing data including monthly rent, price per square foot per month, price per square foot per annum, security deposit, maintenance charges, and parking fees. We capture property specifications such as carpet area, built up area, floor number, total floors, ceiling height, loading dock availability, power backup capacity, and lift access. We extract lease details including minimum lease duration, lock in period, rent escalation clauses, and subletting policies. We also capture location intelligence such as business park name, nearby transit stations, airport proximity, highway access, and zoning information. For example, we can extract office space listings across any target city globally with floor plates larger than a specified size. We can extract price per square foot data for warehouse properties near a specific highway or logistics corridor. We can also extract coworking desk prices, meeting room rates, and membership terms from flexible office providers across multiple platforms.
We build custom commercial extraction pipelines based on your target countries, cities, commercial property types, data fields, source platforms you specify, and extraction frequency from weekly to monthly. Delivery options include commercial listing datasets, lease term summaries, price per square foot benchmark reports, property specification matrices, and API feeds into your commercial brokerage or investment platforms. With our extracted data, commercial brokers match corporate clients with suitable properties faster. Real estate investors evaluate commercial asset valuations using current market listings from any source. Facility managers track competing office spaces in their building's micro market. And proptech platforms power commercial real estate search tools with fresh, structured extraction outputs from any geography.
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