Dataworkz

What Dataworkz does

Dataworkz provides a platform for enterprise teams to put AI agents into production. It allows for the creation of governed AI agents from any workflow, with built-in controls, audit trails, and ROI measurement. The platform offers a library of pre-built agents and the ability to build custom ones from natural language prompts. It connects to existing enterprise systems with over 100 connectors and supports various deployment models including SaaS, Dedicated, and In-VPC. Dataworkz emphasizes security and compliance with SOC 2 Type II certification, chunk-level RBAC, and comprehensive audit trails.

Products

• Dataworkz PlatformA comprehensive platform for building, deploying, and managing enterprise AI agents with built-in governance, audit trails, and ROI measurement. It includes connectors, an AI-ready information layer, an agentic framework, and managed operations.
• Agent BuilderA tool within the Dataworkz Platform that allows users to build agents using plain English, code, or both, with a visual editor, chat interface, and built-in testing.
• Agent HubA component of the Dataworkz Platform for observability and improvement of agents, capturing interactions and allowing for new use cases to be added.
• RAG BuilderA wizard-driven, no-code tool for building Retrieval Augmented Generation (RAG) agents, allowing for ingestion, indexing, and citation-backed responses.
• Invoice Validation AgentAn agent that verifies invoices end-to-end, extracting fields, matching to contracts, validating hours and billing terms, and routing exceptions for approval.
• Regulatory Lineage AgentAn agent that extracts column-level lineage from Pentaho, SQL, and COBOL pipelines and publishes Collibra-compatible outputs for audit readiness.
• Call Deflection AgentAn agent that builds Spark jobs from DB2 CDC data and loads results through client portal APIs to deflect high-volume client calls.
• Financial Advisor AssistantAn agent that surfaces account context, prior interactions, and next-best-actions for financial advisors during client conversations.
• Travel Claims ProcessorAn agent that assists with processing travel insurance claims, including submission, validation, and status updates.
• KYC Document ReviewAn agent that reads onboarding documents against KYC rule sets, routes ambiguous cases, and produces an audit trail.
• Engineering Change AgentAn agent that reviews engineering change requests against quality records and routes exceptions to a human approver.
• Submission Lineage AgentAn agent that traces the lineage of regulatory submissions across CMC, clinical, and quality systems for audit readiness.
• Customs HTS ClassifierAn agent that classifies imports against the Harmonized Tariff Schedule, suggests duty codes, and flags ambiguous cases.
• ERP Exception HandlerAn agent that catches and triages ERP processing exceptions such as missing fields, mismatched POs, and blocked vendors.
• Document Data ExtractorAn agent that retrieves data elements from specified documents based on a query schema.
• Spark Generation Job BuilderAn agent that converts plain-English data requests into PySpark jobs, executes them on Databricks, and returns the run output.

Key capabilities

• Agentic AI for the Enterprise
• Enterprise AI Governance
• Enterprise Data Pipelines
• Business Orchestration and Automation Technologies
• Pre-built agent templates
• Custom agent building from natural language prompts
• 100+ pre-built connectors
• Governance, audit trails, and ROI per agent built-in
• Runs in your VPC (or other deployment models)
• SOC 2 Type II certified
• Deterministic or reasoned execution
• Managed authentication
• Full audit trail on every action
• Field-level lineage
• Permission-aware (chunk-level RBAC)
• Measurable outcomes for every workflow (ROI, observability, A/B testing)
• Plain-English designer + pro-code SDK
• Multi-step work orchestration
• Two execution modes: Reasoned Plan and Deterministic Plan
• Scenarios for bounded toolsets
• Visual Editor for agent construction
• Chat Interface for agent refinement
• Built-in Testing for iteration
• Agent API for integration (REST API, embeddable)
• LLM-agnostic
• A2A and MCP-native
• Encryption at rest and in transit (AES-256, TLS 1.3)
• Customer-managed encryption keys (CMK/BYOK)
• Defense in depth (Network, Identity, Data, Model, Audit layers)
• VPC peering and PrivateLink
• SAML/OIDC SSO, SCIM provisioning, MFA enforced
• BYO LLM, self-hosted models, air-gapped inference
• Tamper-evident audit log with SIEM export
• Deployment options: Managed SaaS, Dedicated, In-VPC
• Multi-region failover
• 99.99% uptime for dedicated tenants
• Restartable pipelines from any step

Use cases

• Turn any workflow into a governed AI agent
• Extract column-level lineage from data pipelines
• Deflect high-volume client calls
• Verify invoices and route exceptions
• Assist financial advisors with client conversations
• Process travel insurance claims
• Review KYC documents and produce audit trails
• Review engineering change requests
• Trace lineage of regulatory submissions
• Classify imports against Harmonized Tariff Schedule
• Triage ERP processing exceptions
• Retrieve data elements from documents
• Convert plain-English data requests into PySpark jobs
• Advisor enablement (scaling senior knowledge)
• Regulatory and audit work (data lineage, change control)
• Operations and reconciliation (invoice/securities recon, call deflection)
• Engineering productivity (change-control automation, code generation, test automation)
• Mainframe and modernization (COBOL intelligence, API factories)
• IT operations and service desk automation
• Document intelligence and reconciliation (PO matching, supplier docs)
• R&D and clinical knowledge surfacing with citations
• Clinical and operational data pipeline creation for AI-ready insight
• Insights management for HCPs & payers
• Brand intelligence, competitive monitoring, earned-media analytics, journalist affinity graphs, early crisis detection
• Customer support knowledge agent for L1 ticket resolution

AI approach

Dataworkz provides a platform for building, deploying, and managing AI agents for enterprise workflows. It offers pre-built agents and allows users to build custom agents using natural language prompts or a pro-code SDK. The platform connects to existing enterprise systems, provides governance, audit trails, and measures ROI per agent. It supports both reasoned (dynamic) and deterministic execution plans for agents and is LLM-agnostic, allowing customers to bring their own models.

Tech named: LLMs, PySpark, Spark, Databricks, Pentaho, Collibra, ClarityServer, DB2 CDC, ISO 20022, Kafka, SFTP, JIRA, GitHub, Confluence, SharePoint, Spring Boot, API, Snowflake, MongoDB, CockroachDB, Couchbase, OpenAI, Anthropic, vLLM, Llama 3.2-3B, Neo4j, pgvector, Elasticsearch, Modal, Pub/Sub, AWS KMS, Azure Key Vault, GCP KMS, SAML, OIDC, SCIM, WAF, VPC peering, PrivateLink, AES-256, TLS 1.3, SIEM, Alteryx, Tableau, Epicor

Industries served

• Financial Services
• Capital Markets
• Manufacturing
• Life Sciences
• Wealth Management
• Healthcare
• Marketing Technology
• Medical Equipment Retail

What it says sets it apart

• Agents go live instantly
• Platform connects to existing enterprise systems with governance, audit trails, and ROI per agent built-in
• Runs in customer's VPC (or other deployment models)
• SOC 2 Type II certified
• Fortune 200 enterprises run 20+ agents in production
• 100+ pre-built connectors
• Deterministic or reasoned execution with managed auth and full audit trail
• Data stays where it lives, no data movement required
• ROI per agent, measured per run
• Simple, transparent pricing with free starter tier
• Fully managed, global cloud platform on AWS, Azure, and GCP
• Field-level lineage and audit trail per agent
• Permission-aware (chunk-level RBAC)
• Deployment models that keep data inside customer perimeter
• Audit trail on every action with timestamp, user, and source
• Aligned with 21 CFR Part 11, GAMP 5, and GxP requirements for Life Sciences
• One integrated stack for connectors, information layer, agentic framework, and managed ops
• Governed end to end with chunk-level RBAC, full traces, and audit at every layer
• Fully extensible with MCP, custom APIs, custom skills, or own codebase
• Agents are open and embeddable, built on standard protocols (A2A, MCP)
• Export agents as standalone containers (no lock-in)
• Ability to build agents without an ML team (no-code RAG Builder)
• Months of pipeline turnaround compressed into hours
• Restartable pipelines from any step