Govern. Optimize. Trust.
Impetus Prism™
Unified AI-powered Observability & Cost Management for the Intelligent Enterprise.
Cloud and data platform costs are spiraling. Visibility is fragmented. Agentic AI is raising the stakes. Impetus Prism is the industry’s only AI-enabled platform that unifies observability and optimization across your entire data and cloud ecosystem — with native support for AWS, Microsoft Azure, Google Cloud, Databricks, and Snowflake.
The Problem
Cloud costs are spiraling, and data platforms are too complex to manage manually.
Three problems compound each other in every enterprise AI programme:
Fragmented Visibility
Teams lack unified visibility. Multiple dashboards, siloed tools, and disconnected insights hide what drives performance vs what drains it.
Reactive Cost Management
Inefficiencies and SLA risks only appear too late — after the impact. Teams can’t tie every dollar spent to a business outcome or data product value.
Manual Operations & Testing
Testing agents and optimizing complex queries manually limits scaling. Operational control requires an AI-driven, automated approach.
What Prism does
Key capabilities
360-Degree Visibility
Get full visibility into cost, performance, and pipelines across multi-cloud (AWS, Azure, Google Cloud) and data platforms (Databricks, Snowflake) with granular chargeback mapping.
FinOps & Cost Intelligence
Predict future spend, detect cost anomalies early, and optimize workloads with context-aware recommendations – via SQL Maestro and Prism’s conversational interface.
Agentic DataOps
AI agents continuously monitor, optimize, and heal your data platform — automating query tuning, incident triage, and SLA management with pre-approved autonomous actions.
AI Agent Validation
Systematically validate agent behavior across complex scenarios using precision synthetic data, catching failures and enforcing compliance before agents reach production.
Monitor & Optimize
Prism Observability Platform
Unified intelligence beyond traditional tools. The only AI-enabled platform that centralizes observability and cost optimization across your entire multi-cloud and data platform estate.
Impetus Prism unifies cost visibility, performance monitoring, and AI-driven optimization across AWS, Azure, Google Cloud, Databricks, and Snowflake — in a single control plane. It maps costs down to resources, workloads, teams, and business units with built-in chargeback/showback capabilities, and surfaces anomalies and right-sizing opportunities before they impact budgets or SLAs.
PrismIQ
Conversational Cost Intelligence—ask in plain English and get real answers. GenBI-powered dashboards enable intuitive cost exploration and unified reporting across AWS, Azure, Google Cloud, and Databricks.
SQL Maestro™
Leverage SQL Maestro™ to zero in on resource-draining queries, get optimization recommendations for right-sizing, and continuously tune new queries as real-world production traffic hits.
Platform Coverage
Impetus Prism™ features extensive coverage of industry-leading cloud and data platforms, including AWS, Azure, Google Cloud, Databricks, and Snowflake to provide a unified, holistic lens into your resource, performance, and cost metrics.
Govern / Generate
SynthIQ
Realistic data for every test. Zero PII exposure. SynthIQ generates business-accurate synthetic datasets from your actual schemas, enabling AI agents to be tested at scale without ever accessing production data.
Data Echo Mode
Data Echo Mode recreates the behavioral shape of production data without copying sensitive records. It preserves distributions, relationships, cardinality, null patterns, referential constraints, and edge-case frequency, ensuring test datasets behave like the real enterprise environment while remaining PII-free.
Precision Pro Engine
Precision Pro Engine generates high-fidelity synthetic data for accuracy-critical scenarios such as agent validation, migration certification, regulatory testing, and adverse-case simulation. Teams can define scenario constraints, expected outcomes, and coverage targets, then produce repeatable datasets that expose failures before production.
Metapulse
Metapulse profiles source schemas and sample data to extract quality scores, statistical patterns, PII risk indicators, domain entities, cardinality, outliers, and relationship signals. Its profiling output serves as the intelligence layer that guides safe synthetic data generation and downstream validation.
Schema Forge
Schema Forge builds schema-aware synthetic data structures that preserve keys, joins, data types, table relationships, and business constraints. It helps teams generate complete test environments, not just isolated mock rows—so pipelines and agents can be validated against realistic multi-table behavior.
Param Sense
Param Sense learns the operational parameters that make generated data useful: valid ranges, seasonality, thresholds, business-rule limits, channel patterns, product hierarchies, and scenario variables. It turns synthetic data generation into a controlled testing surface where teams can dial up edge cases, volumes, and risk scenarios on demand.
Mismatch RCA
Mismatch RCA compares generated data, expected patterns, and test outcomes to identify why a scenario failed. It flags missing constraints, broken mappings, unrepresentative distributions, schema mismatches, and data-quality gaps, then feeds those insights back into SynthIQ and the testing backlog.
Govern / Validate
SynthIQ’s Validation Harness
The independent validation harness that tests your agents against industry ground truths before they reach production. Positive, negative, and adversarial test suites ensure responsible AI policies are enforced.
It provides a structured testing environment where AI agents run against SynthIQ-generated data across comprehensive scenario suites. Every agent must pass a defined quality gate before deployment.
Govern / Operate
IntelliOps
IntelliOps deploys a suite of specialized AI agents across your data platform that continuously monitor performance, detect anomalies, and execute pre-approved corrective actions without waiting for human intervention. From query optimization to pipeline healing to cost management, IntelliOps makes your data platform self-managing.
Query Performance Agent
Continuously monitors slow-running queries and automatically applies optimization recommendations.
Pipeline Healing Agent
Detects pipeline failures, diagnoses root causes, and executes pre-approved remediation steps automatically.
Cost Management Agent
Monitors cloud data spend and eliminates wasteful compute, storage, and query patterns in real time.
Optimization
SQL Maestro™: Identifies expensive queries and recommends or auto-applies cost and performance optimizations.
Databricks smart sizing: Automatically right-sizes data clusters based on workload patterns to reduce costs and improve performance.
Monitoring & Intelligence
IntelliOps unifies platform telemetry, job history, query performance, data quality, SLA status, and incident patterns into a single intelligence layer. It detects anomalies early, translates operational risk into business terms, and prioritizes actions most likely to protect cost, reliability, and user experience.
Incident Management & SRE
IntelliOps supports incident response with automated triage, root cause analysis, runbook recommendations, escalation routing, and post-incident learning. It integrates with ITSM and SRE workflows, enabling teams to move from fragmented alerts to governed, evidence-backed resolution.
How
it works
Platform
integrations
Proven Results
Ready to trust and scale your AI operations?
In a 2-hour Prism Assessment, our engineers will review your current AI agent testing gaps, identify where IntelliOps can immediately reduce operational burden, and give you a concrete path to autonomous data operations.