Shivacha AI Analytics
Ask questions of your data in plain language — with governed, verifiable answers.
Metric A
Trend
Metric B
Trend
Anomalies
None
Overview
An AI analytics product for natural-language questions over your warehouse, automated insights, forecasting and anomaly detection — with semantic layers, permissions and query transparency.
The problem
Business users wait on data teams for simple questions, while dashboards go unused because they do not answer the question at hand.
The solution
Shivacha AI Analytics lets users ask questions in plain language, generates governed queries against a semantic layer, shows the query and data behind every answer and surfaces anomalies proactively.
Feature modules
What's inside
Natural-language query
Questions translated into governed SQL.
Semantic layer
Business definitions for consistent metrics.
Insights
Automated summaries and drivers analysis.
Forecasting
Time-series forecasts with confidence intervals.
Anomaly detection
Alerts on unusual changes.
Governance
Row-level permissions and query logs.
Product preview
Designed for operators and end users.
- Transparent queries
- Metric definitions
- Permission-aware answers
- Charts on demand
- Scheduled insights
- Forecasts
- Anomaly alerts
- Warehouse-native
- Understand requestIntent: refund · order #4821
- Retrieve policyRefund policy v3 · 2 sources cited
- Call toolsorders.lookup · payments.status
- 4Human approvalRefund above auto-approve limit
- 5Execute actionpayments.refund
- 6Respond & logCustomer reply · audit trail
Tool call
orders.lookup({
order_id: "4821"
}) → { status: "delivered",
amount: 42.00 }Approval required
Refund 42.00 to original payment method
Architecture
Built to integrate and extend.
Modular services behind stable APIs, deployed into your environment.
Specifications
Deployment, security and integration
Integrations
- Data warehouses
- BI tools
- Slack / Teams
- Identity providers
Security
- Data stays in your environment where required
- Role-based access and document-level permissions
- Prompt-injection and output guardrails
- Full audit logs of prompts, tool calls and outputs
- Encryption in transit and at rest
Deployment
- Your cloud account (AWS, Azure, Google Cloud)
- Private VPC with self-hosted models
- Managed deployment operated by Shivacha
- Hybrid: hosted UI, private data plane
Customisation
- Model and provider selection
- Custom tools and integrations
- Brand, tone and guardrail policies
- Workflow and approval rules
- Custom evaluation sets
Use cases
Who launches with it
- Executive Q&AFast answers to business questions.
- Operations monitoringAnomalies in key metrics.
- Finance analysisVariance and driver analysis.
- Sales analyticsPipeline and performance questions.
See it in action
Request a tailored demo for your use case.
Demos are tailored to your markets, partners and integration requirements.
Custom engineering
Extend it with our services
AI Data Solutions
Data engineering for AI: pipelines, warehouses, feature stores, vector indexes and governance that make AI systems accurate.
Learn moreMachine Learning Development
Custom machine learning models for prediction, scoring, forecasting and recommendation, deployed and monitored with MLOps.
Learn moreAI Integration Services
Integrate AI capabilities into existing products, ERP, CRM and internal systems through APIs, events and embedded UI.
Learn moreRelated products
Works well with
Shivacha Copilot Kit
Embed a context-aware AI copilot into your product or internal tools.
Learn moreShivacha AI SaaS Starter
The foundations of an AI SaaS product — ready to build your differentiation on.
Learn moreShivacha ERP
Modular ERP for finance, inventory, procurement and operations.
Learn moreLearn more
Related thinking
Permission-aware enterprise knowledge assistant
How we design a RAG assistant that answers from thousands of internal documents while respecting every user's access rights.
Learn moreAgentic claims intake with human approval
A reference design for an AI workflow that reads claim submissions, extracts and validates data, and prepares cases for adjusters.
Learn moreAI development cost: what you pay for when you build an AI product or agent
Model fees are rarely the main cost. Data preparation, evaluation, integrations and guardrails decide both the budget and whether the system works.
Learn moreFAQ
Frequently asked questions
How do users trust AI-generated numbers?
Every answer shows the generated query and source data, based on governed metric definitions.
Does data leave our warehouse?
Queries run in your warehouse; only necessary context is sent to models, per your policy.
Which warehouses are supported?
Common cloud warehouses and PostgreSQL.
Request a product demo.
See how Shivacha AI Analytics fits your business, and how we would customise and deploy it.