Simplify VerifiableGranularPrivate Real-Time Multi-Party Controlled Data Sharing

No code, zero trust platform for easy and secure data exchange

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Remove burden on IT, data and engineering teams to enable complete data sharing

Minimize your data liabilities

while increasing data utility and reducing costs by 80%

Collaborate across boundaries

with internal & external partners without revealing raw data

Harden your tech-stack

with zero trust, privacy preservation and lineage

Break your data silos in minutes

with no-code, automated data workflows and self service

Expedite data agreements transparently

with smart contracts and immutable transactions

Establish single source of truth of data

while meeting varied and stringent regulations

Who would use
Blockfenders and why?

Benefits

01

Ubiquitous, easy, granular and interoperable data sharing with minimal liability

02

Accelerate digital transformation with maximum data utility

03

Protect data resources rather than just security perimeter

04

Data verifiability, trust, transparency, integrity and privacy preservation

05

Automated data workflows with no code, raw data isolation

06

Prevent data manipulation and protect data from insider threats and external attacks

More Benefits

How it works?

Blockfenders (preview) facilitates a zero trust and zero knowledge data architecture, making it easier to automate secure, real-time data exchange between two or more parties with minimum liability. Now you can share streaming data and data at rest across cloud, on-premise or hybrid environments in any organization or geography granularly and in a controlled manner. Blockfenders keeps the data trustworthy with verifiability, privacy enhanced with de-identification and encrytion, and context aware with lineage. With Blockfenders, you can connect your favorite analytics, visualization or SQL query tool for deeper insights.

SOURCE

Any application or data source in any environment.

Application Data Operational Data
Transactional Data Analytical Data

OPERATIONS

SOURCE

OPERATIONS

DESTINATION

Any application or data source in any environment.

Any application or data destination in any environment.

Application
Data

Operational
Data

Transactional
Data

Analytical
Data

1. CONNECT

Use pre-existing connectors, APIs or Kafka to connect to application or data source

2. INGEST & PROCESS

Ingest data and structure it into tables. Optionally preserve privacy using masking and encryption techniques.

Data ingestion & Table services

  • Ingest data from source of choice
  • Structure into tables, data catalog, ACID, compaction, clustering, de-duplication, indexing and more

Data Masking

  • De-identify or anonymize fields of choice

Encryption

  • Encrypt fields of choice

3. SHARE

Share data easily with internet or external parties using pre-existing connectors, APIs or Kafka without writing any code.

Granularity, multi-party, real time

  • Share data granularly with multiple parties in real-time

Verifiability with Zero Knowledge Proof and Zero Trust

  • Achieve zero trust and zero knowledge with on demand or continuous data verification using cryptography.
  • Verify without revealing actual data.

Control sharing with password less authentication and access, and end-to-end encryption of data

  • Asymmetric public-private key based passwordless authentication and authorization.
  • Encrypt data end-to-end for controlled sharing.

Lineage

  • Immutable, tamper evident full context and history

Exchange Data Externally or Internally

Monetization

Query, Analytics, Visualization

DESTINATION

Any application or data source in any environment.

Exchange Data Externally or Internally
Monetization
Query, Analytics, Visualization

Use Cases

Zero trust, privacy enhanced data
clean rooms

Multi-party data exchange with
verifiability of data

Data monetization, commercialization,
leasing and subscription

Immutability, chain of custody and zero
trust for data accessibility

How to Get Started?

Schedule a 20
minutes demo

Demo

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demonstrate
a use case

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Solutions

FAQs

Existing mechanisms of data exchange and sharing do not minimize data liability because they are inefficient and broken. They include direct access to data, creating data views, ETLing, RPC (remote procedure calls), static APIs and FTP (File Transfer Protocol) are inefficient and brIt is hard to achieve controlled and granular sharing with these mechanisms and break data silos. They are cost prohibitive, mostly manual, and need data and engineering resources which are not easy to find. To facilitate data sharing, these mechanisms require investments in specialized infrastructure like data warehouses and integrations across multiple technologies which is technically complex. They do not allow cross platform data exchange leading to vendor lock-in. Lastly, these mechanisms do not provide ongoing verifiability and immutable history leading to data disputes. With these current tools, achieving data agreements is challenging.

Current data security and access solutions are centralized which leads to a single point of failure. The data transaction history and logs are not tamper evident or tamper proof, thus leading to data disputes. The solutions are perimeter of security based and do not protect the actual data resources. Many ransomware attacks and insider threats occur regularly in spite of using some of the best identity, security and access control solutions increasing the risk of sensitive, PII and restricted data getting exposed and leading to reputation damage. Further, these tools fail at providing ongoing data verifiability.

Blockfenders is a no-code data exchange and access platform. You do not have to write code or use programmatic mechanisms like FTP, RPC, APIs to facilitate data sharing. With a few configurations and clicks, and within minutes, you can start exchanging and accessing data in a granular and controlled manner. Blockfenders automates data workflows and eliminates your dependency on IT, data and engineering teams to share data, thus save costs on these resourcing and unblocking your existing teams.
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