SARASWA CONSULTING LLP
Sectors as filed: IT Consulting
The website is as filed on the register. We have not checked that it resolves. Something wrong with this record?
Six things we look for on every record: DPIIT recognition, a CIN, a website, a description, a logo and a funding signal. Not held here: DPIIT recognised and Logo.
Where this is
District
Bengaluru
Karnataka
Startup India records the district. We do not have a street address for this company, and we will not invent one.
No point is drawn, because we do not have one.
Geocode confidence: medium
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What this record amounts to
SARASWA CONSULTING LLP is a Startup India record we can place no finer than Bengaluru district, which holds 34,244 records in this snapshot. 4,430 of those records are filed under IT Services, 13% of the district. The one funding signal on it is: Self-declared on the government form, unverified.
Every figure above is counted from the 2026-08 snapshot and is the same number the page it links to prints.
In their own words
2. Background and Justification With the rise of pandemics and infectious diseases, contactless medical disease identification has become critical to reduce the spread of infections and to ensure rapid, accurate, and non-invasive diagnosis. Traditional diagnostic methods often require physical contact and laboratory analysis, which can be time-consuming and risk-prone. The integration of AI and IoT technologies offers the potential to revolutionize the way medical conditions are identified, providing safer, faster, and more accurate diagnostic solutions. 3. Objectives 1. Develop an AI-based System for Disease Identification: Create algorithms capable of analyzing medical data and identifying diseases without physical contact. 2. Integrate IoT Sensors for Real-Time Data Collection: Deploy contactless sensors for gathering physiological data such as temperature, heart rate, and respiratory patterns. Create algorithms capable of analyzing medical data and identifying diseases using human aura. 3. Design a User-Friendly Interface for Healthcare Providers: Develop an intuitive interface for easy access to diagnostic results and patient data. 4. Validate System Efficacy through Clinical Trials: Conduct extensive clinical trials to test system accuracy and reliability across different demographics and diseases. 4. Methodology 4.1. System Development 4.1.1. AI Algorithm Development • Data Collection: Gather large datasets from existing medical records and sensors to train the system. • Machine Learning Models: Develop models capable of analyzing patterns in physiological data and identifying indicators of disease. • Deep Learning Techniques: Use neural networks to enhance pattern recognition and diagnostic accuracy. 4.1.2. IoT Sensor Integration • Sensor Selection: Choose non-invasive sensors capable of measuring vital signs such as body temperature, heart rate, and oxygen levels. • Data Transmission: Use wireless technologies for real-time data transmission to the central system. 4.1.3. User Interface Design • Healthcare Interface: Create a dashboard for healthcare providers to view patient data and diagnostic results. • Patient Application: Develop a mobile app for patients to monitor their health and receive diagnostic feedback. 4.2. Clinical Validation 4.2.1. Pilot Studies • Initial Testing: Conduct small-scale trials in collaboration with local clinics to test system functionality. • Feedback Collection: Gather feedback from healthcare professionals and patients to refine the system. 4.2.2. Large-Scale Trials • Clinical Trials: Conduct large-scale clinical trials to assess system accuracy, reliability, and user satisfaction. • Data Analysis: Analyze trial data to evaluate system performance and identify areas for improvement. 4.3. Implementation and Deployment 4.3.1. System Rollout • Deployment Strategy: Plan the phased rollout of the system in selected hospitals and clinics. • Training Programs: Provide training for healthcare providers on using the system effectively. 4.3.2. Ongoing Support and Maintenance • Technical Support: Establish a support team to address technical issues and provide system updates. • User Support: Offer continuous support for healthcare providers and patients using the system. 5. Expected Outcomes 1. Improved Diagnostic Accuracy: Enhanced accuracy in identifying diseases without physical contact. 2. Faster Diagnosis: Reduced time for diagnosis, leading to quicker treatment and better patient outcomes. 3. Increased Patient Safety: Minimized risk of infection and cross-contamination during the diagnostic process. 4. Enhanced Healthcare Efficiency: Streamlined diagnostic processes, allowing healthcare providers to focus on treatment and care.
Written by the company on its public Startup India profile. Not verified by us.
What the record says
- CIN
- ABA-0952
- Registered on Startup India
- 2025
- Self-declared stage
- Prototype
- Industry
- IT Services
- IT Services in Bengaluru
- 4,430 records
- District
- Bengaluru
- State
- Karnataka
Funding signals
We hold evidence classes, not events. There is no amount and no date here because we do not have them, and a class says only where the company was named. 3,674 of the 34,244 records in Bengaluru carry a signal of some class.
- Self-declared on the government form, unverified
The neighbourhood
This record carries no locality line, so the district is the finest ring we can place it in.
What we do not know
- no incorporation date
- no address beyond the district
We have no liveness signal for any company on this site: no filings feed, no revenue, no check that the website still resolves. A record existing here means a record exists, not that a business is trading.
Is this your company?
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