askEdgi FAQs
FAQs for website
Architecture & Security
How can AskEdgi give insights for cross-functional questions without a data warehouse? AskEdgi connects directly to source systems, pulls only the data needed for a specific question, and analyzes it in a temporary secure workspace.
What about companies that already have a data warehouse? AskEdgi can enhance your warehouse by combining it with non-warehoused data, adding context through metadata. This results in a better User experience.
Do you use your own model or publicly available models like ChatGPT? AskEdgi uses a hybrid approach—combining in-house extensions for governance-aware tasks and secure integration with trusted public LLMs for language understanding. In the current version, we are supporting OpenAI.
Is enterprise data shared with an AI model provider? No. AskEdgi does not send your raw enterprise data to public AI providers. We create a RAG with extended metadata, build queries, and then run them in a secure temporary workspace.
How does AskEdgi answer questions without sharing data with AI providers? By using retrieval-augmented generation (RAG) techniques, AskEdgi keeps data processing internal, feeding only relevant metadata or summaries to the AI model.
What’s the maximum size of data AskEdgi can handle? Up to 100GB per session for uploaded files, with real-time queries on live data sources. AskEdgi can handle about 1TB of data in its workspace. For more limits, please ask for a bigger server capacity.
How do you ensure data security? Data never leaves your environment without encryption, strict access controls, and policy enforcement based on your existing governance setup.
Can I fine-tune the AI responses or SQL generation? Yes. Users can refine, adjust, and override generated queries, with enterprise admins able to configure logic templates and recipe behavior.
Is the AI model trained on my data? No. AskEdgi does not train its models on your data. Your data is used solely for in-session processing.
Access, Governance and Compliance
How does AskEdgi ensure data governance and compliance? It enforces access policies, checks permissions before querying data, and logs every query for traceability—all integrated with your governance policies.
Can I control who accesses what data? Yes. Role-based access controls and data-level permissions allow precise governance.
Does AskEdgi log and audit user queries? Yes. Every question, dataset accessed, and action taken is logged for auditing and compliance.
How does AskEdgi handle PII or sensitive data? Sensitive data is automatically detected using metadata classification, and access is restricted according to your governance rules.
How does AskEdgi ensure privacy compliance? Privacy compliance: AskEdgi has integrated compliance features that let you manage the entire privacy compliance.
How does AskEdgi ensure data quality? Using the Data Quality module, you can define your data quality policies and their enforcement. In case the data is of low quality, OvalEdge can restrict its use in AskEdgi.
Value Prop & Features
How is AskEdgi different from using ChatGPT or a traditional BI tool? Unlike ChatGPT, AskEdgi understands enterprise data, access controls, and context. Unlike BI tools, it requires no modeling or dashboards—ask in plain English.
How does AskEdgi reduce time-to-insight compared to traditional methods? It skips ETL, modeling, and dashboard setup—pulling only the needed data and answering in real-time.
What data sources does AskEdgi support? AskEdgi supports most common databases, cloud platforms, ERPs, CRMs, APIs, and Excel/CSV files. See the list of connectors.
Can I upload my own datasets (CSV, Excel, etc.)? Yes. Upload up to 100GB per session and start querying immediately. We support CSV, Excel, and Parque files.
What if users don’t know what questions to ask? AskEdgi offers domain-specific “Recipes” that suggest meaningful questions based on the dataset and context.
How is AskEdgi’s AI better than other platforms like Snowflake or Alation? Snowflake focuses on storage and processing; Alation on cataloging. AskEdgi combines cataloging, querying, AI, and governance for end-to-end insight delivery.
Can AskEdgi handle unstructured or semi-structured data? Yes. Text fields and logs can be analyzed using AI Functions for sentiment, classification, and anomaly detection.
What are Recipes, and how do they benefit both creators and consumers? Recipes are curated question sets with built-in logic. Creators can build and share them; users can apply them instantly for consistent, expert-level insights.
How do AI Functions work? They apply advanced AI models to analyze free-text data inside structured datasets—like detecting sentiment, entities, or errors.
Can it connect to cloud data warehouses like Snowflake, BigQuery, or Redshift? Yes. AskEdgi integrates directly with major cloud data warehouses and supports live querying.
Does AskEdgi integrate with existing data catalogs or governance tools? Yes. It can connect to external catalogs or operate as a full-suite solution with built-in cataloging.
Can I share or export insights with others in my team? Yes. Share results, visualizations, and saved questions across your team.
Can I collaborate with others on the same question or report? Yes. Multiple users can refine questions, co-develop recipes, and track insights together.
Is the data in AskEdgi real-time or scheduled? It supports real-time querying and also allows scheduled refreshes when needed.
Can I trigger data refreshes manually or automatically? Yes. Users can configure both manual and automated refresh options.
Is AskEdgi available as a SaaS or on-prem deployment? AskEdgi is available as a secure SaaS offering; however, it can connect to your data, which is on-prem or in the cloud, using its bridge technology.
AskEdgi Q&A
Unlocking Analytics with AI, Governance, and Zero Warehouse Dependency
What is the core value proposition of AskEdgi? AskEdgi offers a groundbreaking way to interact with enterprise data. Unlike traditional analytics tools or generic AI interfaces like ChatGPT, AskEdgi empowers business users to ask analytical questions in natural language and receive answers instantly—without needing to know where the data resides, how to query it, or whether they have access. The platform connects directly to enterprise systems and leverages metadata cataloging, access management, and AI-driven querying in one seamless interface. It intelligently determines which datasets are relevant, checks governance and access rights, runs the required analysis, and presents results—all in real-time. This makes advanced analytics accessible to everyone in the organization while upholding strict data governance standards.
How is AskEdgi different from using ChatGPT or a traditional BI tool? While ChatGPT allows natural language interaction, it lacks awareness of enterprise data systems, governance rules, and contextual relevance of organizational datasets. Traditional BI tools, on the other hand, require technical skills, data modeling, and often rely on pre-built dashboards connected to a data warehouse. AskEdgi bridges these gaps by:
Allowing users to ask questions in plain English.
Automatically identifying the right data sources across the enterprise.
Validating whether the user is authorized to access the data.
Generating AI-powered queries on the fly.
Returning results in tables, charts, or visual summaries.
In essence, it delivers the simplicity of ChatGPT with the power of enterprise data access, all wrapped in robust governance and metadata intelligence.
What if users don’t know what questions to ask? AskEdgi solves this through “Recipes”—curated sets of domain-specific questions and queries developed by experts. These recipes address common analytical scenarios, such as auditing a general ledger or analyzing procurement performance. Users can simply select a recipe, apply it to their dataset, and receive comprehensive answers—without needing to understand the underlying data structure or query logic. This makes complex analytics not only accessible but also scalable across teams with varying levels of data literacy.
What are the core pillars of AskEdgi’s value proposition? The platform stands on five foundational pillars:
Natural Language Interface: Enables users to interact with data using conversational queries, similar to ChatGPT.
Smart Data Discovery: Automatically identifies which datasets are relevant for a given question—no need to know table names or join logic.
Access Control & Governance: Verifies permissions before data is accessed, ensuring full compliance with internal and external governance policies.
Expert Recipes: Provides a library of reusable, domain-specific question sets that simplify complex analytics.
Instant Analytics Execution: Delivers real-time answers by dynamically generating and running queries, eliminating the need for traditional data warehousing and dashboard building.
AI functions: Analyse textual data within structured data with the help of AI.
How does AskEdgi reduce time-to-insight compared to traditional methods? In traditional environments, getting answers from data typically involves multiple steps: identifying the data source, extracting and cleaning data, loading it into a warehouse, building queries or dashboards, and finally analyzing results. This can take weeks or even months, especially when multiple teams (data engineers, analysts, business users) are involved. AskEdgi collapses this entire pipeline into a single interaction:
Data is pulled only when needed and only for the specific question asked.
Governance checks happen automatically in the background.
Queries are generated by AI and executed in a temporary workspace.
Results are displayed immediately, often within seconds. This agility transforms how business questions are answered—from long cycles to real-time decision-making.
This agility transforms how business questions are answered—from long cycles to real-time decision-making.
Why did organizations previously need a data warehouse, and how does AskEdgi remove that need? Historically, data from various business systems (CRM, ERP, operations) had to be centralized into a data warehouse to enable cross-functional analysis. This process involved:
Manually identifying relevant data.
Building ETL pipelines to move data into a warehouse.
Structuring data models.
Building dashboards or reports.
AskEdgi changes this paradigm. Instead of moving data, it queries it directly from the source and brings it into a secure, temporary workspace only when needed. The platform orchestrates the end-to-end process—from data discovery and access validation to analysis and visualization—without requiring permanent data consolidation. This approach is faster, less expensive, and dramatically more flexible, especially for organizations that lack existing warehouse infrastructure.
How does AskEdgi ensure data quality and compliance if it doesn’t use a centralized warehouse? Although it avoids permanent warehousing, AskEdgi includes robust governance and data quality management. It leverages the OvalEdge data governance engine to:
Enforce role-based access controls.
Check for data sensitivity (e.g., PII, financial fields).
Validate data quality through rules and policies.
Additionally, users can incorporate data quality checks and transformations as part of their recipes or governance workflows, ensuring that insights are both immediate and reliable.
What’s the value for companies that don’t have a data warehouse at all? For organizations without a warehouse—estimated to be 70% of companies—cross-functional analytics is typically out of reach. They’re often limited to what each application can report independently. AskEdgi enables these organizations to perform enterprise-grade analytics by:
Connecting directly to diverse data sources.
Consolidating and analyzing data on-demand, without permanent storage or manual integration.
Applying governance and recipes to ensure meaningful insights.
This unlocks decision-making capabilities that were previously impossible without significant infrastructure investment.
What about companies that already have a data warehouse? Even in companies with data warehouses, often only 30% of enterprise data is stored there. The remaining 70%—spread across SaaS platforms, internal systems, and spreadsheets—remains inaccessible to traditional BI tools. AskEdgi’s value lies in its ability to:
Analyze across both warehoused and non-warehoused data.
Use metadata and catalog intelligence to find relevant datasets even within the warehouse.
Offer superior query generation through context-aware AI that understands data purpose, ownership, and lineage.
Even when other tools provide ChatGPT-like interfaces, they typically lack this metadata context, which limits their analytical power.
How is AskEdgi’s AI better than other platforms like Snowflake or Atlan? Most platforms specialize in either data storage (like Snowflake) or metadata cataloging (like Atlan). Few integrate both with AI-powered querying. For example:
Snowflake provides excellent storage and query execution, but lacks metadata context, so its AI can’t generate optimal queries.
Atlan can build queries from its catalog, but cannot execute them or generate queries as intelligently as AskEdgi.
AskEdgi uniquely combines metadata cataloging, governance, AI-based query generation, and execution—making it a full-stack solution.
This unified architecture enables better data discovery, smarter analytics, and a seamless user experience.
Can AskEdgi handle unstructured or semi-structured data? Yes. Through its AI Functions feature, AskEdgi can analyze text fields and unstructured data embedded in structured datasets. For instance, work order descriptions can be scanned for keywords indicating equipment failure, anomalies, or sentiment patterns. This allows organizations to extract insights from text-heavy records—without needing to pre-process or label them manually—bringing natural language understanding to operational analytics.
What are Recipes, and how do they benefit both creators and consumers? Recipes are predefined, domain-specific analytical playbooks. They consist of:
A set of relevant business questions.
The underlying logic or queries to answer them.
Optional visualizations or data quality checks.
Recipe creators (e.g., auditors, finance experts) can build and test recipes using sample data—even without an enterprise edition. They can then monetize their expertise by listing the recipe for sale. Recipe consumers (e.g., analysts, managers) can purchase and run these recipes directly on their own data—getting expert-level insights without needing deep technical or domain knowledge.
What are the different versions of AskEdgi available? There are two main editions:
Public Edition:
Upload personal files and use public datasets (e.g., weather, government data).
Ideal for students, small teams, or recipe creators.
Recipes can be created, tested, and shared.
Cannot connect to enterprise systems or private data sources.
Enterprise Edition:
Connects to internal systems (ERP, CRM, databases).
Provides complete data cataloging, governance, and recipe execution.
Enables cross-functional analytics at scale within the organization.
Who should use the Public Edition, and what is its key value? The Public Edition is ideal for:
Individual analysts or students experimenting with AI-powered analytics.
Recipe creators who want to build, test, and monetize their domain expertise.
SMBs or teams with limited internal systems who still want to leverage intelligent analytics.
While it doesn’t offer enterprise connectivity, it provides a powerful sandbox for learning, testing, and building analytics skills.
Copyright © 2025, OvalEdge LLC, Peachtree Corners, GA USA
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