Observe, explain and prepare.
- Watch cross-system events and service levels
- Compare evidence against defined rules
- Explain root cause and business impact
- Prepare a safe action or escalation
Practical AI for supply-chain teams
DataShip connects a focused AI agent to approved evidence across Fishbowl and the systems around it. The agent monitors the work, brings the right records together and recommends a safe next action. Your team stays in control of every important decision.
UPC and style attributes match Item 10963. Prepare a validation-only mapping test?
Featured film · 45 seconds
This sample-data film follows a blocked Shopify order through Fishbowl evidence, root-cause explanation, a safe recommendation, human approval and a complete audit record.
The agent notices that a Shopify order did not enter the expected Fishbowl pick-and-ship flow.
The agent notices that a Shopify order did not enter the expected Fishbowl pick-and-ship flow.
The design principle
Useful operational AI begins with trustworthy connections, clear source-of-truth ownership and defined business rules. We build that foundation first, then introduce intelligence where it removes real work and makes decisions easier to review.
What an agent can do
This is not a general chatbot. Each agent gets one defined job, uses approved evidence and sends the recommendation to a named person who owns the decision.
The agent watches Shopify, retailer and Fishbowl order flow, then tells the team which orders are stuck and why.
It can compare the SKU, UPC and item status, suggest the likely correction and prepare a safe test for the order owner to approve.
The agent combines demand, available stock, inbound supply, lots and lead times to surface risk earlier.
It can show which product may stock out, explain the assumptions and recommend a transfer, allocation or replenishment review.
The agent finds missing, expiring or conflicting supplier documents, specifications and quality records.
It can flag a missing certificate or specification mismatch before release, while the authorized quality owner keeps final approval.
The agent turns order, inventory, production and fulfillment activity into a short list of business-critical exceptions.
Each issue arrives with supporting records, likely impact and a named next step so the team can act instead of assembling another spreadsheet.
How it works
The model is only one component. Reliable agents also require deterministic checks, access controls, approval logic, validation and an audit trail.
Orders, inventory, EDI, lots, shipments and documents.
Deterministic checks establish the operating truth.
The agent explains what happened and prepares the next move.
The authorized owner approves, rejects or escalates.
Results are checked and preserved for review.
A practical TraceGains example
TraceGains can hold supplier records, specifications, certifications and quality documents. Fishbowl can own purchasing, receiving, lots, production and inventory. DataShip connects the handoff so each system keeps the job it does best.
Supplier documents, ingredient specifications, certificates and COAs are collected and reviewed in the controlled quality workflow.
The integration passes only the approved operational fields, identifiers and release status needed downstream—and flags missing or expired evidence.
Purchasing, lots, inventory and production stay connected to the right supplier and product status without making Fishbowl the quality-record system.
An agent can explain what is missing or out of date, identify the affected item or lot and route the evidence to the person authorized to decide.
Representative integration pattern; the exact fields, approvals and system boundaries are confirmed during discovery. TraceGains remains the controlled supplier and quality environment, while the agent supports—not replaces—quality judgment.
Built for your environment
DataShip is not tied to one model, hyperscaler or packaged copilot. We design the solution around the systems, security boundaries, operating owners and deployment standards your organization already uses.
Use services such as Amazon Bedrock, Lambda, Step Functions, EventBridge, API Gateway and S3 to connect models, workflows, documents and operational events. DataShip can design the agent around your AWS identity, logging, networking and data-governance standards instead of creating a disconnected AI island.
BEDROCK · LAMBDA · STEP FUNCTIONS · EVENTBRIDGE · S3Integrate through Azure OpenAI, Azure Functions, Logic Apps, Power Automate, Copilot Studio, Fabric and Power BI, with identity and access governed through Microsoft Entra ID. Agents can work alongside Dynamics 365, Microsoft 365 and existing line-of-business applications while preserving the systems that already own each transaction.
AZURE AI · POWER PLATFORM · FABRIC · POWER BI · ENTRA IDWhen an off-the-shelf copilot is not the right fit, we can build a custom agent service around your preferred model provider, APIs, databases, integration middleware and user experience. That can include a dedicated operations console, Teams or email approvals, scheduled workflows, retrieval over controlled documents and private endpoints for existing applications.
YOUR MODELS · YOUR APIS · YOUR DATA · YOUR CONTROL MODELStart with a bounded use case and connect only the evidence it needs. Once it is proven, we can add specialized agents for orders, EDI, inventory, suppliers, warehouse activity and executive reporting—coordinated through shared permissions, escalation rules, observability and audit history.
The interface can live where the team already works: a custom web application, Microsoft Teams, Power BI, email approvals, an operations queue or an embedded experience inside an existing system.
Design a custom AI solution →Governed by design
We scale authority only after the data, controls and operating owner are ready.
Begin read-only and establish confidence against real operating history.
Expose the evidence, business rule, confidence and proposed action.
Route consequential decisions to the named, authorized owner.
Preserve inputs, decisions, actions, validation results and exceptions.
A simple first step
We will map the work, identify the evidence an agent can safely use and define a small proof of value before anyone commits to a broad AI program.
Request an AI workflow assessment ↗Choose a manual, slow or risky process with a clear business owner.
Name where the work begins, where it stalls and which system owns the final record.
Use sample data or read-only access first so the workflow can be proven without production risk.
Agree on a practical result such as hours saved, exceptions resolved or stockouts avoided.
No. Fishbowl remains the operational system of record. DataShip agents work across the handoffs between Fishbowl and connected commerce, EDI, 3PL, supplier and reporting environments.
Only when a client explicitly approves the action, permissions and validation path. We normally begin read-only, add recommendation and approval, then consider narrowly scoped writes after the workflow is proven.
The minimum trustworthy data required for the decision. That can include orders, item mappings, inventory, lots, acknowledgments, shipments or supplier records. We fix source ownership and integration reliability before adding AI.
Each material recommendation should expose its evidence, confidence, business rule, required approver, action result and audit history. If the evidence is insufficient, the agent escalates instead of guessing.
Your next move
Bring us the broken workflow, unreliable forecast, warehouse constraint, reporting burden or difficult integration everyone has learned to work around. Your assessment is senior-led and ends with a practical recommendation, scope boundary and next-step decision.
Request a 30-minute assessment ↗