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Whizur Platform Background

Build AI-powered apps
without custom infrastructure.

Workflows, artifacts, and APIs — already wired.

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Build once. Reuse everywhere.

Three paths. Two fail at scale.

Custom builds take months. One-off scripts break in production. There's a third way.

Custom Build

6+ months to production

  • Bespoke pipelines with no owner
  • Months of infrastructure work
  • Vendor lock-in

Script Sprawl

Works in demo, breaks in prod

  • Unversioned scripts and agents
  • No audit trail or replay
  • Inconsistent outputs

Whizurai

Production in days, not months

  • Pre-built capability packs
  • Every run is auditable and replayable
  • Outputs become reusable primitives
Replayable Auditable Composable

Workflows run. Artifacts persist. APIs serve.

Capability Packs

Pre-built workflows with defined inputs and outputs. Run them. Get artifacts.

Slackumentation

Ingest Slack threads. Output searchable artifacts and APIs.

Outputs
Searchable artifacts
Structured datasets
Query APIs
View Details

K8s Incident Intelligence

Ingest cluster events. Output root-cause analysis and runbooks.

Outputs
Incident summaries
Root-cause artifacts
Runbook primitives
View Details

Support Intelligence

Ingest docs and tickets. Output cited answers via API.

Outputs
Answer dataset
Prompt presets
Support API
View Details

Release Intelligence

Ingest PRs and commits. Output release notes and changelogs.

Outputs
Release summaries
Change datasets
Customer notes
View Details
View all packs

Example: Support Intelligence

Input: 1,247 support docs + 3 months of tickets

Day 1: Ingest docs → generate dataset

Day 2: Create prompt presets → validate answers

Day 3: Deploy API → serve cited responses

Output: Support API
Artifacts: Dataset, Prompts, Workflow
Time: 3 days

How Whizurai works

Three steps. No custom infrastructure.

1

Run workflows

Execute pre-built or custom workflows on your data

2

Get artifacts

Datasets, prompts, and policies are created automatically

3

Serve via API

Query artifacts and trigger workflows from your app

Every run is versioned, auditable, and replayable.

What you can build

Common patterns. Pre-built workflows. Production-ready.

Support Intelligence

Docs and tickets → cited answers via API.

Content Intelligence

Products and catalogs → enriched metadata and recommendations.

Trust & Safety

Content → policy decisions with full audit trail.

Research Agents

Queries → structured reports from bounded workflow execution.

Workflow execution

Steps run. Artifacts are created. Everything is versioned.

Workflow Run Timeline

Created Artifacts

TYPENAMECREATED
Workflow
1,247 files processed
4:27:56 AM
Workflow
Structured dataset
4:27:56 AM
Dataset
ds_support_v1.2.0
4:27:56 AM
Prompt Preset
preset_support_qa_v3
4:27:56 AM
Workflow
artifact_support_workflow_2024_12_28
4:27:56 AM
Status: RunningTotal: 4/5 steps

Production features

Every workflow run is observable, auditable, and replayable.

Workflow-level observability

Full input/output audit trails

Versioned intelligence

Scales on proven infrastructure

Infrastructure handled for you

Start building

Run your first workflow in minutes. No infrastructure setup required.

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