askEdgi FAQs
Overview & Capabilities
What is askEdgi?
askEdgi is an AI-powered analytics assistant designed to simplify data exploration and insight generation. It connects to enterprise datasets or public datasets, interprets natural-language questions, and produces insights, summaries, analytics, and visualizations without requiring technical skills or manual coding.
What problems does askEdgi solve?
askEdgi reduces reliance on analysts and technical teams, accelerates insight generation, shortens investigation time, and eliminates the need for complex SQL or BI tools. It improves decision-making by providing instant, context-rich answers generated from data, metadata, or uploaded files.
What types of insights are generated by askEdgi?
askEdgi provides descriptive summaries, trend analysis, distribution analysis, exception detection, comparisons, patterns, correlations, and narrative explanations. Depending on the mode selected, it also produces dataset profiling, schema explanations, and visualization-based insights.
How does askEdgi understand questions?
askEdgi uses a domain-aware natural language processing engine combined with metadata context. It maps the question to the correct dataset, fields, relationships, and filters, then runs automated logic or recipes to extract accurate answers from the underlying data or metadata.
What datasets can be used with askEdgi?
askEdgi works with public datasets, uploaded files, enterprise data sources, and metadata repositories. The availability of each dataset type depends on the edition—Public, SaaS Data Analytics, SaaS Metadata Analytics, or On-Prem.
Can askEdgi explain data structures?
Yes. askEdgi provides field-level definitions, relationships, profiling insights, constraints, and schema details in Analytics Mode. It also interprets table purposes, usage patterns, lineage, and dependencies to offer a clear understanding of the dataset.
Does askEdgi provide visualizations?
Yes. askEdgi generates appropriate charts, tables, and visual summaries based on the nature of the question or recipe. The visualization selection is automated but can be influenced by variants and recipe types.
How does askEdgi support decision-making?
askEdgi produces clear narratives explaining results, highlights key observations, identifies root causes, and recommends next steps. This reduces manual interpretation effort and ensures data-backed decisions across business scenarios.
Modes & Guided Interactions
What is Smart Mode?
Smart Mode provides guided question-based interactions. It interprets natural questions, understands context, and delivers summarized insights or visual responses. It is best suited for quick analysis and high-level business questions.
What is Discovery Mode?
Discovery Mode automatically examines datasets and produces an overall summary. It highlights dataset characteristics such as record counts, distributions, null patterns, dominant categories, and data quality indicators.
What is Analytics Mode?
Analytics Mode delivers deeper analytical exploration, including field-level profiling, segment analysis, joins, correlations, and multi-level insights. It supports detailed analytical reasoning and is suitable for advanced investigation.
How does askEdgi handle context across multiple questions?
askEdgi maintains conversation context within the session. It remembers the dataset, filters, and insights requested earlier, enabling follow-up questions without reselecting sources or providing repeated instructions.
What are the variants in askEdgi?
Variants are specialized response formats that adapt the analytical outcome. Examples include:
• Summary variant
• Compare variant
• Trend variant
• Distribution variant
• Detailed Analysis variant
Variants help frame insights in the most suitable analytical perspective.
How does askEdgi choose the right dataset for a question?
askEdgi uses context, metadata assessments, usage patterns, glossary associations, and table-level relevance scoring. This ensures correct table selection even when the dataset name is not mentioned.
How are errors handled during question interpretation?
askEdgi provides validation prompts when insufficient context exists, clarifies missing details, or suggests alternate datasets. This prevents incorrect analysis and ensures reliable insight generation.
Can askEdgi perform follow-up comparisons or refinements?
Yes. Follow-up questions such as "compare with last month", "show by region", or "filter only top contributors" are automatically applied on top of earlier insights in the same session.
Recipes & Marketplace
What are recipes in askEdgi?
Recipes are reusable analytical workflows. They automate multi-step tasks such as model application, data transformations, multi-table joins, rule checks, visual reports, or advanced comparisons. Recipes can be published, monetised, or reused.
What types of recipes are available?
Recipe types include:
• Data Recipes
• Metadata Recipes
• Workflow Recipes
• Prompt Recipes
• Transformation Recipes
Each type addresses different analytical or workflow requirements.
How do recipes execute in Public Edition?
In the Public Edition, recipes run inside a temporary workspace with limited compute. Inputs can be public datasets or uploaded files. Once executed, outputs are accessible only within the workspace unless published to the Marketplace.
How do recipes execute in SaaS editions?
In SaaS Data Analytics, recipes run on enterprise connectors with full data availability. In SaaS Metadata Analytics, recipes execute only on the OvalEdge (-1) connector using metadata instead of data.
Can recipes be published for monetisation?
Yes. Public Edition allows creators to publish recipes to the Marketplace. Consumers subscribe to recipes, and earnings are credited based on usage and plan type.
What is included in recipe governance?
Recipe governance includes tagging, versioning, access restrictions, data security enforcement, workspace isolation, and execution logs. This ensures safe experimentation without exposing enterprise data.
How are recipe inputs validated?
askEdgi checks dataset availability, file formats, field types, metadata relevance, and execution limits before running a recipe. Any missing requirements are highlighted through guided prompts.
What details are provided after recipe execution?
Execution results include insights, summaries, charts, data tables, downloadable files (Public Edition), and narrative interpretations, along with activity logs and cost summaries.
Knowledge Agent, Governance & Security
What is the Knowledge Agent?
The Knowledge Agent is a guided help system powered by OvalEdge documentation and metadata intelligence. It assists in performing operational tasks, provides step-by-step help, and explains modules, workflows, and processes across the platform.
How does the Knowledge Agent assist with platform navigation?
It guides users through tasks such as creating glossaries, updating metadata, raising access requests, configuring lineage, building data stories, and managing data quality workflows. Every instruction is context-aware and reference-backed.
How does askEdgi ensure data security?
askEdgi uses workspace isolation, encrypted communication layers, RBAC validation, metadata-only interactions with AI engines, and strict access enforcement. No raw enterprise data is transferred outside the organisation.
What governance principles shape askEdgi?
Key governance principles include secured access controls, lineage awareness, data classification checks, audit logging, and permission-based dataset visibility. These ensure compliant and controlled analytics.
How does askEdgi manage enterprise connectors securely?
Connectors enforce authentication, masked views, schema-based restrictions, metadata validation, and secure pushdown processing. This prevents unauthorised access or exposure.
How is privacy maintained during AI-based processing?
askEdgi provides a metadata-first architecture, ensuring only enriched metadata is shared with the AI orchestration layer. Enterprise data remains within secure systems, preventing external leakage.
What is workspace isolation in askEdgi?
Each analysis or recipe runs in a separate workspace with controlled limits. This isolates operations, prevents cross-project interference, and ensures secure data handling.
What auditing does askEdgi support?
askEdgi logs recipe executions, dataset usage, consumption costs, workspace history, billing details, and all user-level interactions. These logs support governance, compliance, and monitoring.
Editions, Subscriptions & Usage
What is the Public Edition of askEdgi?
The Public Edition allows exploration of public datasets, file uploads, recipe creation, shared workspaces, and monetisation opportunities. It operates on limits defined by the subscription plan.
What is the SaaS Data Analytics Edition?
This edition integrates with enterprise data sources, supports full data workloads, allows advanced analysis, and executes all recipe types within a secure enterprise environment.
What is the SaaS Metadata Analytics Edition?
This edition focuses only on metadata. It enables discovery, profiling summaries, lineage analysis, and metadata-only recipes without accessing enterprise data.
What is the On-Prem Edition?
On-Prem deployment runs within the enterprise's internal environment. It supports only metadata analytics and metadata recipes to meet strict data security and compliance standards.
How does subscription management work in Public Edition?
Users can subscribe to tiered plans based on compute limits, token usage, recipe execution capacity, and monthly billing thresholds. Spend limits, reminders, and consumption rules are applied through automation jobs.
What is included in the Usage Dashboard?
The Usage Dashboard displays compute consumption, recipe execution costs, AI token usage, spend trends, plan limits, and historical charts. It provides transparency for billing and execution patterns.
How is billing calculated in Public Edition?
Billing is based on compute usage, recipe runs, workspace consumption, AI token usage, and plan-specific allocations. Automated system jobs calculate charges, generate reminders, and lock usage if limits are exceeded.
What benefits do paid plans offer?
Paid plans unlock higher compute limits, additional recipe runs, more workspace access, extended file size support, monetisation privileges, and enhanced collaboration features.
Getting Started & Basic Operations
Uploading & Working With Data
How do I upload a file and ask questions about it?
Files can be uploaded from My Workspace using drag-and-drop or the Browse to Upload option. Once the file appears in the workspace list, questions can be asked directly in the chat using the uploaded file as the analysis source.
What file formats and sizes are supported?
askEdgi supports CSV, Parquet, XLSX, and JSON file formats. Each file can be up to 1 GB in size. Larger files or unsupported formats must be prepared or converted before upload.
How do I select datasets manually if askEdgi picks the wrong dataset?
The correct dataset can be pinned using the Pin to Focus option. Pinning restricts all subsequent analysis to the selected dataset and prevents automatic switching to other available sources.
Asking Questions
How does askEdgi understand questions?
askEdgi interprets natural language by combining metadata, dataset structure, pinned objects, and session context. This allows accurate mapping of questions to the correct tables, fields, filters, and relationships.
What kinds of questions cannot be answered?
Questions cannot be answered when required datasets are not available in the workspace, calculations are unsupported, relationships between fields are unclear, or access permissions are restricted.
How should I phrase questions for the best results?
Questions should clearly specify the dataset, columns, filters, time periods, and expected output. Clear phrasing reduces ambiguity and improves accuracy, especially when multiple datasets exist.
Why do answers vary between attempts?
Results may vary due to changes in pinned datasets, context carried from previous questions, filters applied implicitly, or differences in phrasing. Dataset structure and sampling behavior can also influence results.
Downloading & Exporting
How do I save results, export tables, or download visualizations?
Download options are available with generated tables and charts. These options allow saving outputs in supported formats.
What are the limitations on downloads or exports?
Downloads and exports are restricted to system-generated outputs such as tables, charts, summaries, and files produced during analysis or recipe execution. Source datasets and raw enterprise data are not exported directly.
Exports may be limited by file size, visualization type, workspace limits, and subscription constraints. Certain complex or interactive visuals may not be available for download. Download options apply only to supported output formats generated within the workspace.
Can I download the underlying data used in the insight?
Yes. askEdgi allows exporting the tables generated during analysis.
Viewing Behind-the-Scenes Logic
How do I view the SQL / logic behind the answer?
askEdgi offers the generated SQL or analytical logic behind insights within the analysis panel. This provides transparency into how results are derived.
Can I customize or edit the generated SQL?
Yes. Generated SQL can be edited and re-executed to refine logic, apply additional filters, or validate assumptions.
Permissions, Access & Security
Dataset Access Controls
Do I need specific permissions to access certain datasets?
Yes. Only datasets permitted through metadata governance and role-based access controls appear in the workspace and are available for analysis.
What if my organization has masking rules?
Masked columns remain masked during analysis. All masking rules defined in metadata governance are enforced automatically and cannot be bypassed.
How does masking or role-based access control affect results?
Results reflect only the data you are allowed to view. Restricted fields are excluded from calculations, visualizations, and exported outputs.
Why can my colleague see datasets I cannot?
Dataset visibility depends on role assignments, access policies, and metadata governance rules, which may differ across users.
Data Privacy & Compliance
Can askEdgi see personally identifiable information (PII)?
askEdgi processes only accessible data. Masked or restricted PII fields remain hidden and are not exposed in results or AI processing.
Can administrators see what I ask?
Administrators can access governance and audit logs. These logs include usage activity, execution metadata, dataset references, recipe runs, timestamps, workspace consumption, and system events.
Administrators cannot view conversational intent, reasoning, personal interpretations, or analytical thought processes behind questions. Free-form exploration context and user reasoning are not exposed through administrative logs.
Does askEdgi store user questions or learn from them?
Question logs are maintained for operational visibility based on system settings. These logs are not used to train external AI models.
Does askEdgi retain or log my uploaded files?
Uploaded files remain within the workspace until removed. Files are not shared outside the workspace.
Does askEdgi comply with enterprise data governance policies?
Yes. All access, masking, lineage, and permissions follow the enterprise metadata governance framework.
Data Modification Safety
Can askEdgi modify enterprise data?
No. askEdgi performs read-only analysis and does not write back or modify source systems.
Can askEdgi trigger workflows that change data indirectly?
No. All workspace actions are limited to analysis and do not trigger data-changing workflows in enterprise systems.
Recipes, Marketplace & Advanced Features
Creating & Running Recipes
How do I create my first recipe?
Start from the Recipes module, choose a recipe type, add inputs, validate, and run the recipe.
What should I do if a recipe fails to run?
Execution logs should be reviewed, inputs validated, and selected datasets or metadata objects confirmed.
What does each recipe type mean?
Data Recipes: Operate on datasets
Metadata Recipes: Operate on metadata objects
Prompt Recipes: Generate text-based outputs
Workflow Recipes: Define multi-step automated actions
How do I validate whether my recipe inputs are correct?
Check the recipe input fields and ensure required objects exist and are compatible with the selected recipe type.
Publishing & Governance
How do I publish a recipe to the marketplace?
Submit the recipe through the publish option. It undergoes admin-level validation before being listed.
How do recipe approvals or validations work?
Approvers review the recipe, its inputs, and its behavior before approving.
Can I share recipes with my internal team only?
Yes. Recipes can be published only internally, depending on governance settings.
Troubleshooting Recipe Issues
Why did my recipe execution exceed compute or time limits?
Large inputs or complex logic may exceed workspace limits or compute capacity.
How do I debug recipe output or logs?
Execution logs provide detailed step-by-step information, including errors and warnings, to support troubleshooting.
Collaboration, Sharing & Cross-Team Usage
Sharing Analysis
Can I share my analysis with stakeholders?
Yes. Analysis results such as charts, tables, and summaries can be exported and shared outside the platform.
Can I export an entire analysis session as a report?
Yes. Export options allow downloading summaries in supported formats.
Can multiple users collaborate inside the same workspace?
No. My Workspace is personal. Collaboration is enabled through shared outputs, recipes, or projects.
Context & Continuity
How does askEdgi handle conversation context?
askEdgi maintains an active context using pinned datasets, filters, and prior interactions within the session.
Can I reset or clear the context if something is misunderstood?
Yes. Unpin all datasets or start a new question thread to reset context.
How long is conversational context retained?
Context persists for the duration of the session or until manually cleared.
Troubleshooting & Error Recovery
Dataset & Query Errors
Why am I seeing a “Dataset not found” message?
The dataset may be unpinned, removed, renamed, not added to the workspace, or you may not have the required access permissions.
What should I do when askEdgi returns incomplete or empty results?
Verify columns, filters, and dataset selection. Some datasets may not contain matching data.
What to do when askEdgi misinterprets my question?
Rephrase the question with specific fields or table names.
Visualization & Output Issues
Why did askEdgi choose a certain visualization?
askEdgi selects a visualization based on the question intent, data types, and dataset structure.
What if my download or visualization fails?
Retry the generation. Large or unsupported visuals may need simplified queries.
Performance & Limits
Expected response time.
Responses arrive within seconds but may vary with dataset size and workspace load.
What happens when my workspace limits are exceeded?
askEdgi alerts you and restricts additional additions until items are removed or the workspace is upgraded.
What happens if I exceed my plan’s compute allowance?
Processing may pause or stop until additional compute capacity is available.
Are there limits on the number of questions or tokens?
Yes. Limits depend on your plan’s compute and usage policies.
Usage, Billing & Account Management
Monitoring Usage
How do I view my usage consumption and limits?
Usage panels or notifications indicate compute, storage, and workspace thresholds.
How do I know when I am close to running out of compute?
askEdgi alerts you when usage is near the threshold.
Billing & Consumption Rules
What happens if I exceed my compute or token allowance?
Tasks may pause or require an upgrade before continuing.
How is compute charged for long-running recipes or queries?
Compute charges are based on processing duration and workspace configuration.
Workspace & History Management
Can I deactivate or delete my workspace or history?
Uploaded objects can be removed. The workspace remains as a fixed personal environment.
Can I delete or anonymize my question logs?
Logs are handled according to enterprise retention policies.
How do I wipe uploaded files or temporary datasets?
Use Remove All from Workspace to clear all files and folders.
Enterprise-Specific Capabilities & Extensions
Data Governance Features
Can askEdgi help with data quality issues?
Yes. askEdgi analyzes datasets to identify anomalies, inconsistencies, missing values, and unusual patterns.
Can askEdgi provide lineage-aware insights?
Yes. When datasets are linked to the catalog, askEdgi leverages lineage metadata to understand upstream sources, downstream dependencies, and transformations. This ensures insights reflect the full data flow and dependency context.
Can askEdgi read glossary definitions for better answers?
Yes. Business glossary terms and definitions are used to interpret intent and improve semantic understanding during analysis. Glossary terms enhance contextual accuracy, even though glossary objects are not added directly to My Workspace.
Operational Questions
Can askEdgi run scheduled or automated insights?
Scheduled execution is not supported within the workspace. However, Recipes provide a structured mechanism for repeatable and semi-automated analysis workflows.
Can askEdgi trigger alerts based on thresholds?
Automatic alerts are not triggered directly within the workspace. Threshold-based logic can be implemented within recipes, but notification delivery is handled outside the workspace.
Additional Questions
Reliability & Transparency
How does askEdgi validate its answers?
askEdgi validates outputs by applying dataset filters, lineage context, metadata constraints, and generated SQL or analytical logic. This ensures results are consistent with workspace data and governance rules.
Does askEdgi show confidence scores?
Confidence scores are not displayed. Transparency is provided through access to generated SQL, logic, and visible data outputs for verification.
How often is the AI model updated?
AI model updates follow platform release cycles and enhancements delivered through regular product updates.
Safety & Ethical Use
What safeguards prevent misuse of sensitive data?
Safeguards include role-based access control, data masking rules, metadata-driven permissions, workspace isolation, and audit logging. These controls prevent unauthorized exposure of sensitive data.
Can askEdgi hallucinate or generate incorrect answers?
Occasional inaccuracies are possible, especially with ambiguous questions or incomplete context. Verification through generated SQL, pinned datasets, and visible outputs is recommended.
What should I do if I suspect an incorrect insight?
Generated SQL and logic should be reviewed, pinned datasets validated, and the question rerun with clearer filters or dataset references.
Help & Support
How do I request new features or enhancements?
Submit enhancement requests through your administrator or support portal.
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-warehouse 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 the 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
Last updated
Was this helpful?