Systems | Development | Analytics | API | Testing

[AgentSpot Showcase Series] Solutions Engineering Allocation Workflow

See how this AgentSpot workflow takes the manual work out of SE allocation. It looks at the request, region, expertise, and calendars to recommend the right SE for the job. Then it sends the recommendation straight to Slack. What is AgentSpot? AgentSpot is multiplayer AI for your business. Anyone can build, share, and collaborate with AI agents connected to your company’s data, context, and tools.

[AgentSpot Showcase Series] - Product Decoded Customer Success Agent

Watch how Liz Johnston uses AgentSpot to turn technical product updates into digestible, ready-to-share content for her customers. The Product Decoded agent pulls together key details and creates a Google Doc, branded PDF, and email-ready HTML. One prompt, three deliverables ready to go. What is AgentSpot? AgentSpot is multiplayer AI for your business. Anyone can build, share, and collaborate with AI agents connected to your company’s data, context, and tools.

[AgentSpot Showcase Series] - Deal Sherpa Sales Agent

See how AgentSpot can bring real-time support into the sales process. Deal Sherpa pulls together account context, surfaces gaps and risks, and recommends what to do next. See how it works and what it looks like in action. What is AgentSpot? AgentSpot is multiplayer AI for your business. Anyone can build, share, and collaborate with AI agents connected to your company’s data, context, and tools.

From Dashboards to AI Agents: Huel's Analytics Journey

You’ve rolled out a modern data stack, built self-service dashboards, and empowered your team to ask their own questions. Job done, right? Not quite. The data landscape is shifting rapidly beneath our feet, which makes it critical to understand how to build your AI for BI platform so you can scale and navigate technology evolutions.

Source to Target Data Mapping in Astera Centerprise

Watch an AI agent in Astera Centerprise map data from Dynamics CRM to Snowflake, field by field, with data transformation, in a no-code interface. This demo walks through a real data mapping scenario: a sales team's pipeline in Dynamics CRM (accounts, deal stage, close date, and deal amount in multiple currencies) needs to land in Snowflake every night for revenue and forecast dashboards. See how the agent reads both schemas, matches fields automatically, standardizes currency, and schedules the pipeline to run unattended.

Governed Data Pipelines: Meeting SOC 2 and Regulatory Requirements

Organizations moving healthcare, financial, or EU-resident data through an ETL pipeline face a specific constraint: the pipeline itself has to be compliant, not just the destination warehouse. Every hop a record makes from source system to transformation layer to warehouse, is a point where sensitive data can be exposed, mishandled, or logged somewhere it shouldn't be. That makes the governance model of the pipeline tool itself part of the compliance picture, not an afterthought to it.

How to Build a Marketing Dashboard in One Conversation

Describe the metrics in plain English. AI Analyst builds them, assembles the dashboard, and next month’s report starts from this month’s build. To build a marketing dashboard in one conversation, describe each metric you need to AI Analyst inside Databox in plain English, confirm the components it proposes, and ask for a dashboard assembled from the metrics you defined.

From Experiment Tracking to AI Factory: What Changes When AI Becomes a Shared Enterprise Capability

The term “AI factory” is usually introduced as a hardware story: racks of accelerators, high-speed networking, and validated reference designs. That part is real, but it is not the part most organizations struggle with. The harder shift is operational. Moving from AI as a set of individual experiments to AI as a shared, governed capability that many teams depend on changes how compute is allocated, how environments are built, who owns the platform, and how the work is governed.