Reasoned Plan
For work where the next step depends on the last one.
Best for
Investigative research, exception handling, customer questions that don't fit a script.
Dataworkz Platform
One platform for enterprise agents.
Dataworkz gives engineering, data, and IT teams the building blocks to deploy agentic AI across business functions. Connect enterprise systems. Define workflows in plain English. Run agents with the controls production teams need.
100+ connectors
Three deployment models
Agent and program-level observability
04
Agent-Level ROI
Traces · analytics · audit trail
03
Built by Your Team
Plain-English designer + pro-code SDK
02
Agentic Workflows
Reasoned + deterministic plans
01
AI-Ready Enterprise Data
100+ connectors · knowledge graph
Built around your enterprise data.
Most agent projects stall before production because the hard work sits outside the model. Your data is scattered. Tools need governed access. Workflows need traces your team can inspect.
Dataworkz brings the data layer, agent framework, builder experience, and operating layer into one platform. Your team can start with one workflow, then reuse the same connectors, tools, memory, and controls across the next one.
AI-Ready Enterprise Data
Make your data usable by agents.
Your data lives in documents, databases, APIs, tickets, and business systems. Dataworkz connects those sources, extracts meaning, and gives agents the context they need to act.
Agentic Workflows
Run work across reasoning and rules.
Enterprise workflows rarely fit one pattern. Some steps need reasoning. Others need deterministic execution, approvals, and audit trails.
Two execution modes. Both auditable.
Deterministic Plan
For work that runs the same way every time.
Best for
Invoice processing, change control workflows, securities reconciliation, any SOP your team already runs.
Scenarios
Keep agents focused on the work they're meant to do.
Scenarios cluster related use cases with a bounded toolset. Instead of exposing every tool to every question, your agents see only the tools relevant to the task at hand.
Scenario: invoice.reconcile
extract.line_items
match.po
validate.budget
Outside the scenario
crm.search
code.generate
On the platform
Reasoned plans
Deterministic plans
Scenarios
Managed authentication
Tool execution
Memory and instructions
A2A and MCP-native
LLM-agnostic
Built by Your Team
Build agents the way your team works.
Business users need a builder they can use. Engineering teams need code-level control. Business units need their own environments, tools, and access boundaries.
You
Build an agent that processes contractor invoices. Cross-check hours and rates against the PPM system. Route exceptions to a human approver.
Agent Builder
I'll set up an invoice reconciliation agent with 5 steps: extract, match.po, match.contract, validate.budget, route_to.approver. Connecting to your PPM via Snowflake.
You
Add a step to flag anything 3% over budget.
Agent Builder
Adding budget threshold to validate.budget…
Describe what you need. Refine in chat. Ship the agent.
See the agent under construction.
Click any section to edit scenarios, tools, and configuration directly.
Talk to the Agent Builder.
Request changes across scenarios. Ask for suggestions on tools.
Iterate before anything goes to production.
Run tests, compare versions side-by-side, catch regressions.
Make your agent accessible where teams already work.
Expose via REST API. Embed in website, Slack, Salesforce, or any internal tool.
On the platform
Plain-English Agent Designer
Pro-code SDK
Agent templates
Tools, memory, and instructions
Business-unit isolated environments
Three deployment models
Agent-Level ROI
Measure every agent you run.
Once agents touch production work, your team needs more than logs. You need to know what each agent did, what it cost, where it saved time, and which decisions need review.
On the platform
Agent-level traces
Program-level analytics
Tool-call history
Workflow outcomes
Audit trail
Exception review
Governance controls
200+
Agents in production across 7 workflows at a Fortune 200 financial services firm. Dataworkz runs across status center automation, regulatory lineage, COBOL support, and API-enabled workflows. Every agent traceable. Every decision auditable.
Your agents work where your team already works.
A2A, MCP, REST, and container export. Your agents integrate with the ecosystem you already run.
Agents that hand off to other agents, across platforms.
Agent-to-Agent protocol lets your agents coordinate with agents running on other platforms. One handles retrieval, another decision-making, another output routing, with a shared trace across every step.
Your agents as MCP tools. Other MCP tools inside your agents.
Dataworkz acts as both MCP server and MCP client. Expose your agents as tools to any MCP-compatible system, or invoke external MCP tools inside your workflows. Ecosystem-native from the start.
Programmatic control over every agent, every trace, every output.
Full REST API coverage. Create agents, invoke them, retrieve execution traces, pull ROI data. Your developers build against the API the same way they build against any other enterprise service.
Export your agent. Run it on your own infrastructure.
Agents built on Dataworkz can be exported as standalone containers and self-hosted. No platform lock-in. Build, validate, and deploy wherever your infrastructure requires.
Deployment
Choose where Dataworkz runs.
Your security model should not bend around an agent platform. Dataworkz supports managed SaaS, single-tenant cloud, and in-customer VPC deployment.
Managed SaaS
Managed SaaS
Multi-tenant. Available immediately.
Run on Dataworkz infrastructure. Shared infrastructure, separated data and compute per customer. Dataworkz handles patches, upgrades, scaling, and uptime.
Dedicated SaaS
Dedicated SaaS
Single-tenant. Available immediately.
Single-tenant deployment in Dataworkz cloud. Dedicated compute, dedicated storage, dedicated network. Same managed experience as multi-tenant, with the isolation your compliance team needs.
VPC Deployment
VPC Deployment
Inside your cloud. Custom timeline.
Deploy Dataworkz inside your own VPC. Your data never leaves your environment. Your network policies, your IAM, your monitoring. Dataworkz runs as software inside the perimeter your security team already governs.
The same controls across every deployment. SOC 2 Type II and CASA Tier 2 certified. RBAC at the platform, agent, and chunk level. Managed authentication into your existing IAM. Audit logs your auditors can actually use. Whichever deployment model you choose, the security posture is the same.
Your security, compliance, and ops teams will actually say yes.
Observability that traces every decision. Authentication that inherits your existing policy. Versioning, monitoring, and rollback built into the platform. Not bolted on.
Observability
Every action logged. Every decision explainable.
Production debugging without the guesswork.
Full execution traces for every agent run. Your operations team sees what the agent did, what data it retrieved, what decision it made, and what it output, step by step. When something goes wrong in production, the trace tells you where and why.
Full execution traces
Step-level logging
Explainable decisions
Managed Auth
One auth layer. Inherited permissions.
No separate AI access policy.
Dataworkz inherits authentication from your existing identity infrastructure. Your RBAC policies apply. Agents don't bypass access controls. They operate within them. Your security team doesn't manage a separate set of permissions for AI.
Centralized auth
Inherited RBAC
No shadow permissions
Prototype to Production
The platform you build on is the platform you run in production.
Same environment. Same governance. Same trace.
Version control, monitoring, rollback, and VPC deployment all part of the platform, not bolted on. Your team moves from prototype to production without switching environments or rebuilding for scale.
Versioning and rollback
Production monitoring
Environment parity
Certifications & security posture
SOC 2 Type II and CASA Tier 2 certified. In-VPC deployment. RBAC at the platform, agent, and chunk level. Encryption in transit and at rest. Full audit trail exportable for compliance review. The same security posture applies across every deployment model.
100+ connectors. The systems your business already runs on.
Cloud data platforms, databases, SaaS apps, vector stores, graph, and LLM providers. Pre-built, configured in minutes, running inside your security perimeter.
Discover integrations
Data platforms & warehouses
Snowflake · Databricks · BigQuery · Oracle · SAP · Amazon S3 · AWS · Azure · Google Cloud
Databases & vector stores
MongoDB · PostgreSQL · MySQL · Redis · Couchbase · Elasticsearch · Neo4j · Pinecone
Apps & business systems
Salesforce · ServiceNow · HubSpot · Workday · Stripe · Zendesk · Notion
Collaboration & code
Slack · Microsoft Teams · Jira · Confluence · GitHub · GitLab · SharePoint · Google Drive · Box
AI, data engineering & BI
OpenAI · Anthropic · Hugging Face · Cohere · Apache Spark · Apache Kafka · Airflow · dbt · Tableau · Looker · Docker · Kubernetes · Terraform
Plus 50+ more across CRMs, data lakes, object stores, and LLM providers — pre-built and configured in minutes.
Get started
Build agents on your enterprise data.
See how Dataworkz connects your systems, runs agentic workflows, and measures ROI at the agent level.
SOC 2 Type II
Deploy in your VPC
Permission-aware by default
30 minutes · Book a demo