48-hour verdict

Delivered outcome · production evidence

Enterprise analytics inside the customer cloud — answers to dashboards in under 60 seconds

Business users were locked out of enterprise data by SQL, fragmented sources, reactive BI workflows, and security concerns about sending sensitive data to third-party AI platforms.

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Delivered outcomeTurns natural-language questions into live dashboards in under 60 seconds and deploys inside the customer's AWS account with zero data egress.

What Zenveus built

The work behind the result.

An AWS-native natural-language BI platform that federates enterprise data through Trino, generates governed dashboards with Apache Superset, pushes proactive insights, and embeds as a white-labeled React experience.

WORKSTREAM / 01

Federated enterprise data access

Connected SQL and NoSQL sources through Trino so users could query distributed enterprise data without copying it into a separate AI product.

WORKSTREAM / 02

Governed natural-language analytics

Built the Bedrock agent and guardrail layer around query generation, permissions, explainability, proactive insight detection, and row-level access.

WORKSTREAM / 03

Embedded, customer-cloud delivery

Delivered Superset dashboards and a white-labelled React widget inside the customer’s AWS boundary using ECS, Aurora, ElastiCache, VPC controls, and CloudFormation.

Implementation stackCapabilities used in delivery
Reactembeddable React widgetTrinoApache SupersetAWS BedrockBedrock AgentsBedrock GuardrailsAgentCoreECS FargateAurora PostgreSQLElastiCacheCloudFormationVPC deploymententerprise IdP integrationRBACSQL and NoSQL connectors.

Engineering takeaway

Enterprise AI analytics becomes defensible when permissions, query generation, visualization, explainability, and model guardrails are enforced inside the customer's own cloud boundary.

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The services behind this outcome.

Start with the part of the system that matches your constraint. We will scope the smallest engagement that creates usable production evidence.

Service / 01

Agentic AI & Workflows

Design grounded agents, retrieval systems, guardrails, and production AI workflows.

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AWS DevOps

Engineer cloud infrastructure, security controls, deployment automation, monitoring, and cost discipline.

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SaaS Development

Build maintainable SaaS platforms with permissions, billing, integrations, and operational tooling.

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