HOW CRUSHBANK ORCHESTRATE CORPORATE WORKS

One lakehouse. Every source your business runs on.

CrushBank's proprietary ingestion layer connects to your ERP, CRM, document management systems, HR platforms, collaboration tools, and any other line-of-business application — pulling data continuously, honoring source system permissions, and normalizing it into a single, unified data lakehouse. Before any AI model, automation, or agent touches your data, CrushBank ensures it is clean, standardized, and structured for the type of work it needs to do.

Once ingested, data is stored in three purpose-matched formats:

Structured.

For analytics, computation, and operational reporting. How many open purchase orders are past their delivery date? What is the margin variance across product lines this quarter? These are structured questions that need structured data.

Unstructured.

The complete, original record is always preserved. Teams can always go deeper, review the source document, and verify any AI-generated output against the raw data it came from.

Vectorized.

For semantic and similarity search. When a team member asks a question in natural language, the vector layer finds the most relevant contracts, reports, policies, and records — not just keyword matches.

CrushBank's orchestration layer determines which format — or combination of formats — best handles each incoming request, automatically routing it to the right search tool without requiring the user to know where the data originally lived or how it was stored.

Source system permissions are honored throughout. CrushBank leverages IBM watsonx's AI governance framework to ensure every result is traceable and auditable — giving your leadership team, compliance function, and end users the ability to trust but verify every AI-generated output.

WHAT ORCHESTRATE CORPORATE CONNECTS

Every source your business runs on — connected, normalized, and ready for AI.

CrushBank Orchestrate Corporate ingests and normalizes data from the full breadth of your enterprise application stack:

  • ERP systems — SAP, Oracle, NetSuite, Microsoft Dynamics and others. Financial records, inventory, procurement, production schedules, and operations data.
  • CRM platforms — Salesforce, HubSpot, and others. Customer records, pipeline data, contracts, interaction history, and revenue intelligence.
  • Document management — SharePoint, Box, Google Drive, and others. Contracts, SOPs, policies, proposals, and reports — unstructured data normalized and made instantly searchable.
  • HR and people systems — Workday, ADP, BambooHR, and others. Workforce data, org structure, performance records, and labor analytics.
  • Collaboration and communication — Microsoft 365, Google Workspace, Slack, and others. Institutional knowledge captured, indexed, and made retrievable across your organization.
  • Line-of-business and custom applications — any industry-specific or proprietary system connected via API or direct integration, including legacy platforms and custom databases.

Industry examples of what this means in practice:

  • Manufacturing: Connect your ERP, production scheduling system, quality management platform, and supplier documents into a single lakehouse — enabling plant managers and operations teams to query across production data, defect history, and supplier performance without switching systems.
  • Supply chain and logistics: Unify order management, inventory, carrier data, and warehouse systems so operations teams can ask real-time questions about fulfillment status, capacity constraints, and vendor SLA compliance — and get answers sourced from all systems simultaneously.
  • Construction: Connect project management, estimating, subcontractor agreements, change orders, and financial systems so project executives can query budget versus actual, open RFIs, and schedule variance across every active project from a single interface.
  • Real estate: Unify lease management, property data, financial systems, and tenant documents so asset managers and finance teams can query rent roll performance, lease expiration exposure, and capital expenditure forecasting without manual report assembly.

WHAT YOU CAN BUILD FROM YOUR DATA LAKEHOUSE

What you can build from your data lakehouse.

Step 1 — Conversational Retrieval

Ask questions in plain language. Get answers from across your entire business — instantly.

With your business data normalized and stored in the CrushBank lakehouse, every team member has instant access to your organization's complete institutional knowledge — without needing to know which system holds the answer, how to write a query, or which report to run. CrushBank follows permissions from each of your applications.

Ask what the current inventory level is for a specific SKU across all warehouses. Ask which contracts are expiring in the next 90 days. Ask what the budget variance is on a specific project. Ask which customers have had unresolved issues for more than 30 days. CrushBank's orchestration layer routes each question to the right format — structured for counts, calculations, and reporting, vectorized for document and contextual retrieval — and returns a synthesized, accurate answer in seconds.

For business leaders and managers, the lakehouse becomes a real-time intelligence layer — ask which teams are over or under headcount targets, which product lines are underperforming against plan, where supplier delays are creating downstream risk, or which accounts have the highest churn probability, and get a precise, data-grounded answer without pulling a single report or waiting for a data analyst to respond.

The practical impact: teams spend less time hunting for information and more time acting on it. New employees access institutional knowledge from day one. Leadership decisions are grounded in unified, real-time data rather than the most recently emailed spreadsheet.

 

Step 2 — Automations and Workflow

Build AI-driven automations and workflows grounded in your own business data — not generic AI inference.

Because CrushBank's automations are built on top of your normalized data lakehouse — not a generic AI model — every automated decision reflects your organization's actual operational patterns, business rules, and historical data. The result is automation that performs consistently and accurately, without the unpredictability of a model that has never seen your specific business context.

CrushBank Orchestrate Corporate enables automation across the full range of your business workflows:

  • Document generation. Automatically generate reports, summaries, compliance documentation, and business records using your lakehouse data as the source — eliminating manual document assembly and ensuring every output reflects current, accurate data.
  • Approval and routing workflows. Trigger automated approval chains, escalation paths, and notifications based on conditions in your business data — a purchase order exceeding a threshold, a contract approaching expiration, a project milestone missed.
  • Data monitoring and alerting. Set conditions against your normalized lakehouse data and automatically alert the right people when thresholds are crossed — inventory below reorder level, a supplier SLA at risk, a budget line exceeding variance tolerance.
  • Cross-system data synchronization. Automate the flow of normalized data between systems — ensuring records stay current across your ERP, CRM, and line-of-business applications without manual intervention or fragile point-to-point integrations.

Beyond CrushBank's built-in automation capabilities, your team can design and deploy fully custom automations and workflows using tools like n8n or Langflow — a powerful open-source workflow automation platform that connects directly to your CrushBank data lakehouse. With n8n, your teams can build visual, no-code and low-code workflows that trigger on lakehouse data, call your LLM of choice, and execute actions across any connected system — all governed by the permissions and audit controls built into the lakehouse. This means your organization is not limited to what CrushBank ships: you can build bespoke automations tailored to your specific industry, operational processes, and business rules, using your own normalized data as the engine from day one.

Step 3 — AI Agents

Deploy autonomous agents that monitor your business data continuously — and act on what they find.

AI agents built on the CrushBank data lakehouse do not wait for a team member to ask a question. They run continuously against your normalized business data — surfacing patterns, detecting anomalies, and triggering actions before problems escalate or opportunities go unnoticed.

Because agents operate directly on your lakehouse — not on live source systems — they can analyze the full depth of your historical and real-time business data simultaneously, without impacting the performance of your ERP, CRM, or other applications.

Examples of agents your organization can build and deploy from the CrushBank lakehouse:

  • Contract and compliance monitor. Continuously scans your document lakehouse for contracts approaching key dates, missing signatures, non-standard terms, or compliance gaps — alerting the right stakeholders before deadlines are missed.
  • Financial anomaly detector. Monitors your financial data for transactions, variances, or patterns that fall outside established norms — surfacing potential errors, fraud indicators, or budget overruns for review before they compound.
  • Supplier and vendor risk agent. Tracks supplier performance data, delivery history, and contract terms to flag vendors at risk of SLA breach, enabling procurement teams to act proactively rather than reactively.
  • Customer health monitor. Analyzes CRM, billing, and interaction data to identify customers showing early signs of churn, dissatisfaction, or unresolved issues — giving account teams the intelligence they need to intervene at the right moment.

 

Beyond these pre-built agents, your team can design and deploy fully custom agents tailored to your specific business priorities. Using tools like n8n alongside your CrushBank lakehouse and the LLM of your choice — OpenAI, Anthropic Claude, Google Gemini, IBM watsonx, or any compatible model — your developers and operations teams can define the conditions agents monitor, the thresholds that trigger action, and the workflows they initiate, all grounded in your organization's own governed, normalized data. The lakehouse is the foundation — the agents and automations you build on top of it are limited only by your operational imagination.

 

BUILD ON YOUR OWN GOVERNED DATA LAKEHOUSE

Your data. Your LLM. Your workflows. Fully governed.

CrushBank Orchestrate Corporate is not a closed platform — it is a governed data foundation that your organization can build on. Every capability CrushBank ships is designed to be extended, customized, and connected to the tools, models, and workflows that fit your organization's specific needs.

What this means in practice:

  • Bring your own LLM. CrushBank is fully model-agnostic. Connect OpenAI GPT, Anthropic Claude, Google Gemini, IBM watsonx, Mistral, or any compatible model to your normalized lakehouse and immediately improve the accuracy, relevance, and reliability of every output — because the model is working from clean, unified, organization-specific data rather than public internet knowledge.
  • Build custom documentation and knowledge bases. Use your LLM of choice to generate, maintain, and update internal documentation — SOPs, training materials, compliance records, product specifications — sourced directly from your lakehouse data and kept current as underlying data changes.
  • Build custom agents and automations with n8n or tool of choice. n8n's visual workflow builder connects directly to the CrushBank lakehouse API, enabling your team to design multi-step automation and agentic workflows without writing infrastructure code. Trigger on lakehouse events, call your LLM, execute actions across connected systems, and log every step back to the lakehouse for governance and audit.
  • Analyze and retrieve with precision. Build custom analytical queries, dashboards, and retrieval pipelines on top of your normalized lakehouse — giving your data and business intelligence teams a governed, reliable data layer that replaces fragile point-to-point extracts and manual report assembly.
  • Governed from the ground up. Every custom agent, automation, workflow, and LLM interaction runs within CrushBank's governance framework — source system permissions enforced, all outputs logged and auditable, data residency maintained. Your organization builds with freedom; your compliance team retains full visibility.

GOVERNANCE & SECURITY

Enterprise-grade governance for your most sensitive business data.

CrushBank Orchestrate Corporate is built for organizations where data governance is not optional. Every capability — from conversational retrieval to autonomous agents to custom LLM workflows — is designed to meet the expectations of your compliance, legal, and security teams.

  • Role-based access control enforced at the lakehouse layer, not the application layer. If a user does not have access to a record in the source system, they will not see it in the lakehouse — regardless of which interface, agent, or workflow is making the request.
  • Data residency and sovereignty — your data stays in your environment and is never used to train shared or public models. CrushBank's managed infrastructure supports data residency requirements for regulated industries and geographies.
  • SOC 2 certified — CrushBank's platform is independently audited and SOC 2 compliant, providing your security and compliance teams with the documentation they require for internal governance and vendor risk review.

Your business data is already there. Let's put it to work.

Schedule a demo and see how CrushBank Orchestrate Corporate connects your ERP, CRM, documents, and line-of-business systems into a unified, AI-ready data lakehouse — and gives your organization the governed foundation to build conversational retrieval, AI-driven automations, autonomous agents, and custom LLM workflows on your own data.