Build Trusted Data Products at Agentic Speed
Agniworks helps AWS-focused enterprises turn fragmented data into governed lakehouses, intelligent pipelines, and business-ready analytics — coordinated through one control plane, while your data stays in your own AWS account.
- 1. Connect dataPostgreSQL · Redshift · Snowflake · S3 Tables · OpenSearch
- 2. Understand & governAgni Catalog — profiling, PII, semantic search
- 3. Design the lakehouseAI-generated Bronze / Silver / Gold
- 4. Generate pipelinesAWS Glue & PySpark, aligned to the model
- 5. Deliver Apps & InsightsGoverned consumption via the shared Hub
The data-to-decision lifecycle is broken
Getting from raw sources to trusted analytics still means stitching together separate products, handoffs, and specialist teams — and hoping nothing drifts out of alignment along the way.
Disconnected tools and teams
Data discovery, architecture, engineering, governance, and analytics operate across disconnected tools and teams.
Pipelines drift from the model
Manually built pipelines drift from approved models, creating operational risk and unreliable reporting.
Ungoverned AI
Ungoverned AI introduces new concerns around data exposure, model usage, accountability, and cost.
Business users wait
Business users wait for specialist teams to translate questions into pipelines, dashboards, and applications.
One control plane. A governed path from data to decisions.
Agniworks connects the complete data-product lifecycle — from source discovery and lakehouse design to pipeline deployment and analytical consumption — without disconnecting automation from enterprise control.
Agniworks Data Control Plane
Operated by USTCoordinates the management experience across the lifecycle.
- Identity & roles
- Metadata catalog
- Governance & audit
- Orchestration
- Workflow state
- AI operations
Your AWS Account — Data Plane
You own itData, credentials, processing, and results never leave your account.
- Lakehouse (S3 Tables / Iceberg)
- Glue & PySpark processing
- Secrets Manager credentials
- Athena & analytical results
- Amazon Bedrock (optional)
The outcome is an intelligent, governed foundation for agentic BI — you retain control of data, credentials, infrastructure, processing, and analytical results.
Understand, build, and deliver — grounded in governed metadata
Metadata discovered at the start informs every downstream stage: the catalog shapes the model, the approved model drives the pipelines, and curated data powers Apps and Insights.
Agni Catalog
Understand and govern your data before building on it.
- Reduce data-discovery effort with automated metadata scanning, profiling, semantic search, and AI-generated descriptions.
- Identify risk earlier with PII classification, grain inference, schema monitoring, and profile-drift detection.
- Create a shared business and technical vocabulary with editable descriptions, lineage context, and governed metadata.
Agentic Lakehouse & Pipeline Engineering
Move from business intent to production-ready data infrastructure.
- Accelerate lakehouse design with AI-generated Bronze, Silver, and Gold models grounded in catalog metadata and business requirements.
- Reduce repetitive engineering work with generated AWS Glue and PySpark pipelines aligned to approved models.
- Prevent architecture drift with validations, version controls, lineage, and stale-pipeline blocking.
Apps, Insights & Governed Consumption
Turn curated data into focused analytical experiences.
- Answer business questions faster with constrained SQL, Athena execution, visualizations, and evidence-based narratives.
- Deliver purpose-built data products with generated analytical Apps grounded in governed Silver and Gold data.
- Increase reuse across the enterprise with a shared Hub for published Apps and approved Insights.
The full platform
Secure onboarding & AWS trust
Cross-account trust via a customer-deployed CloudFormation stack and a tenant-specific external ID — explicit and revocable.
Multi-source connectivity
PostgreSQL, Amazon Redshift, Snowflake, Amazon S3 Tables, and Amazon OpenSearch, with credentials referenced from your Secrets Manager.
Tenant-owned AWS Data Catalog
An AWS Glue catalog representation inside your account, so metadata stays available to your native AWS tooling.
Source & profile-drift detection
Compare each refresh to the prior state to surface added or removed tables, type changes, and lost uniqueness before they break reports.
Generated analytical Apps
Describe an app in natural language and publish multi-tab data stories to a runtime hosted in your own environment.
Advanced AppsBeta
A guided, iterative flow with clarifying questions, completeness scoring, evaluation, and immutable revision history.
Insights & the shared Hub
Constrained SQL through Athena produces evidence, visualization, and narrative — shared through a governed internal marketplace.
Agni Assistant
A context-aware guide that explains the current state and next step, running on an Agni-managed control-plane model.
Governance, audit & AI cost visibility
Role-based access, network policies, audit streams, and token / estimated-cost reporting across every AI call.
Choose how much automation and access you grant
The orchestration mode sets the security and operating model — not just feature value. Start where your controls require, and move as trust grows.
Full Automation
Runs cataloging, lakehouse modeling, deployment, and pipeline generation end to end — then deliberately stops before the first pipeline execution, so you decide when data processing begins.
- Principal benefit
- The shortest route to an operational analytics foundation, with minimal coordination between stages.
- Best suited to
- Teams prioritizing speed, standardization, and lower operational effort.
Human-in-the-Loop
The same capabilities with explicit review and approval at important artifact boundaries. Inspect models and generated artifacts before they ever affect infrastructure.
- Principal benefit
- Automation without surrendering architectural or operational control.
- Best suited to
- Architecture review boards, change management, regulated processes, and separation of duties.
Manual
A substantially narrower, read-only trust scope. Agniworks generates downloadable artifacts for the catalog, lakehouse, model, and pipeline stages, and your team deploys them independently.
- Principal benefit
- A low-disruption, low-permission adoption path for security-conscious organizations.
- Best suited to
- Evaluations, highly restricted environments, or teams that retain full execution responsibility.
One platform, aligned to how your teams work
Agniworks reduces the organizational handoffs that normally sit between cloud teams, architects, engineers, analysts, and the business.
For CTOs & Data Leaders
Build a governed data-product operating model without assembling and integrating every platform component internally.
- Compress the path from source onboarding to usable analytics.
- Maintain customer ownership of the AWS data plane.
- Choose Full Automation, Human-in-the-Loop, or Manual operation.
- Track AI activity, model usage, estimated cost, and infrastructure actions.
- Apply approval gates without losing the benefits of automation.
For Data Engineering & Analytics Teams
Spend less time producing repetitive artifacts and more time reviewing architecture, improving data quality, and delivering business outcomes.
- Discover and profile unfamiliar data estates.
- Generate and validate Medallion lakehouse models.
- Produce AWS Glue and PySpark pipelines from approved designs.
- Detect source drift and pipeline-version misalignment.
- Create analytical Apps and Insights from curated data.
Start free. Grow into production. Run it your way.
Three packages, one simple motion: Explore lets you understand what Agniworks can design, Professional lets you deploy with Agniworks, and Enterprise Managed runs it entirely within your AWS environment — operated by UST.
Explore
Understand your data estate and experience Agniworks — no credit card, no broad AWS access.
- Manual orchestration only
- Agniworks-managed AI with an included allowance
- One read-only data source
- Agni Catalog, profiling, PII indicators & grain inference
- One draft lakehouse model with downloadable artifacts
- Agni Assistant & basic AI-usage visibility
Professional
Billed monthly with a 12-month annual commitment.
Self-service production use for an AWS-focused data team, on the hybrid two-plane architecture.
- 12-month annual commitment (monthly invoicing)
- 5 Creator seats · unlimited viewers
- 3 active data sources
- 300 cataloged tables
- 2 lakehouse projects (1 prod, 1 non-prod)
- 15 active pipelines
- 5 Apps & 50 shared Insights
- Bring your own Bedrock account (customer-managed AI default)
- All orchestration modes (Manual, HITL, Full Automation)
- Standard support
Enterprise Managed
A private, client-hosted Agniworks deployment operated as a managed SaaS by UST.
- Single-tenant control plane + data plane in your AWS
- All orchestration modes plus custom approval gates
- Enterprise SSO & identity integration
- Custom connectors & multi-account environments
- Dedicated SLA, service manager & managed operations
- Architecture, security reviews & release management
| Capability | Explore | Professional | Enterprise Managed |
|---|---|---|---|
| Commercial motion | Free trial | Self-serve subscription | Contact Us |
| Architecture | UST control plane; limited connection | Hybrid SaaS | Full platform in your AWS |
| Control-plane operator | UST | UST | UST-managed in your account |
| Orchestration | Manual | Manual, HITL, Full | All modes + custom controls |
| AI models | Agniworks-managed | Bring-your-own Bedrock or Agniworks-managed | Customer-approved models |
| Data sources | 1 | 3 included | Contracted |
| Catalog | Limited | Full | Full & configurable |
| Lakehouse modeling | Draft & export | Full deployment | Full deployment |
| Pipelines | Artifacts only | Generate, deploy, execute | Generate, deploy, operate |
| Apps & Insights | Not included | Included | Included |
| Governance | Basic | Standard enterprise controls | Customer-specific controls |
| SSO | No | Optional / add-on | Included |
| Support | Community / email | Standard | Dedicated SLA |
| Managed operations | No | No | Included |
| Pricing | Free | $1,500/mo · $15K/yr prepaid | Custom |
Prices are initial list hypotheses and may vary by scope. AI consumption on customer-account Bedrock is billed directly by AWS to you.
Answers for security and data teams
No. Agniworks separates the management experience from the operational data plane. Lakehouse tables, processing jobs, secrets, analytical results, and supporting infrastructure remain in your own AWS account.
Agniworks primarily uses metadata and aggregate profiling signals rather than source rows. Credentials remain in customer-controlled AWS Secrets Manager, and you can choose approved Amazon Bedrock models running within your own AWS account.
Agniworks supports greenfield and brownfield AWS environments. Current product surfaces include PostgreSQL, Amazon Redshift, Snowflake, Amazon S3 Tables, and Amazon OpenSearch, with connector availability subject to product configuration.
Yes. Human-in-the-Loop mode introduces review and approval points before generated models and artifacts affect infrastructure. Manual mode provides downloadable artifacts for organizations that retain full deployment responsibility.
The future of data engineering is agentic, trusted, and intelligent.
Build governed data products faster — while keeping control of your data, infrastructure, and AI operations.
See Agniworks in action
Tell us a little about your data estate and what you're trying to solve. We'll follow up to arrange a walkthrough tailored to your AWS environment.
- Runs in your AWS account — you keep ownership.
- Metadata-first AI — no raw-data egress.
- Choose Full Automation, HITL, or Manual.