data-privacy


Privacy Act such as GDPR

The General Data Protection Regulation (GDPR) is a privacy act that was implemented by the European Union (EU) in May 2018. It is designed to protect the personal data of EU citizens and residents by regulating how organizations collect, process, and store their data.

The GDPR applies to all organizations that process the personal data of EU citizens and residents, regardless of where the organization is located. It also applies to organizations that offer goods or services to EU citizens and residents, even if they do not process their data.

The GDPR gives individuals more control over their personal data by requiring organizations to obtain their consent before collecting and processing their data. It also gives individuals the right to access, correct, and delete their data, as well as the right to object to its processing.

Organizations that fail to comply with the GDPR can face significant fines of up to �20 million or 4% of their global annual revenue, whichever is higher.

Steps to comply with GDPR

  • Appoint a Data Protection Officer (DPO) to oversee GDPR compliance
  • Conduct a data audit to identify what personal data is being collected and processed, where it is stored, and who has access to it
  • Obtain consent from individuals before collecting and processing their data
  • Implement appropriate technical and organizational measures to ensure the security of personal data
  • Provide individuals with the right to access, correct, and delete their data, as well as the right to object to its processing
  • Report data breaches to the relevant authorities within 72 hours of becoming aware of them
  • Ensure that third-party processors comply with GDPR requirements

Dataknobs Blog

Showcase: 10 Production Use Cases

10 Use Cases Built By Dataknobs

Dataknobs delivers real, shipped outcomes across finance, healthcare, real estate, e‑commerce, and more—powered by GenAI, Agentic workflows, and classic ML. Explore detailed walk‑throughs of projects like Earnings Call Insights, E‑commerce Analytics with GenAI, Financial Planner AI, Kreatebots, Kreate Websites, Kreate CMS, Travel Agent Website, and Real Estate Agent tools.

Data Product Approach

Why Build Data Products

Companies should build data products because they transform raw data into actionable, reusable assets that directly drive business outcomes. Instead of treating data as a byproduct of operations, a data product approach emphasizes usability, governance, and value creation. Ultimately, they turn data from a cost center into a growth engine, unlocking compounding value across every function of the enterprise.

AI Agent for Business Analysis

Analyze reports, dashboard and determine To-do

Our structured‑data analysis agent connects to CSVs, SQL, and APIs; auto‑detects schemas; and standardizes formats. It finds trends, anomalies, correlations, and revenue opportunities using statistics, heuristics, and LLM reasoning. The output is crisp: prioritized insights and an action‑ready To‑Do list for operators and analysts.

AI Agent Tutorial

Agent AI Tutorial

Dive into slides and a hands‑on guide to agentic systems—perception, planning, memory, and action. Learn how agents coordinate tools, adapt via feedback, and make decisions in dynamic environments for automation, assistants, and robotics.

Build Data Products

How Dataknobs help in building data products

GenAI and Agentic AI accelerate data‑product development: generate synthetic data, enrich datasets, summarize and reason over large corpora, and automate reporting. Use them to detect anomalies, surface drivers, and power predictive models—while keeping humans in the loop for control and safety.

KreateHub

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KreateHub turns prompts into reusable knowledge assets—experiment, track variants, and compose chains that transform raw data into decisions. It’s your workspace for rapid iteration, governance, and measurable impact.

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RAG for Unstructured & Structured Data

RAG Use Cases and Implementation

Explore practical RAG patterns: unstructured corpora, tabular/SQL retrieval, and guardrails for accuracy and compliance. Implementation notes included.

Why knobs matter

Knobs are levers using which you manage output

The Drivetrain approach frames product building in four steps; “knobs” are the controllable inputs that move outcomes. Design clear metrics, expose the right levers, and iterate—control leads to compounding impact.

Our Products

KreateBots

  • Ready-to-use front-end—configure in minutes
  • Admin dashboard for full chatbot control
  • Integrated prompt management system
  • Personalization and memory modules
  • Conversation tracking and analytics
  • Continuous feedback learning loop
  • Deploy across GCP, Azure, or AWS
  • Add Retrieval-Augmented Generation (RAG) in seconds
  • Auto-generate FAQs for user queries
  • KreateWebsites

  • Build SEO-optimized sites powered by LLMs
  • Host on Azure, GCP, or AWS
  • Intelligent AI website designer
  • Agent-assisted website generation
  • End-to-end content automation
  • Content management for AI-driven websites
  • Available as SaaS or managed solution
  • Listed on Azure Marketplace
  • Kreate CMS

  • Purpose-built CMS for AI content pipelines
  • Track provenance for AI vs human edits
  • Monitor lineage and version history
  • Identify all pages using specific content
  • Remove or update AI-generated assets safely
  • Generate Slides

  • Instant slide decks from natural language prompts
  • Convert slides into interactive webpages
  • Optimize presentation pages for SEO
  • Content Compass

  • Auto-generate articles and blogs
  • Create and embed matching visuals
  • Link related topics for SEO ranking
  • AI-driven topic and content recommendations