AI Purchase Requisition & Approval Agent

Departmental purchasing often starts with incomplete descriptions, scattered quotations, and uncertainty about who must approve the request. This custom offering would give employees a consistent intake path while helping procurement teams assemble the information needed for review. Suitable scenarios include equipment requests, professional services, facilities purchases, and internal software procurement.

The agent would organize evidence and identify gaps rather than make commercial decisions. For example, a services request could require a statement of work, contract owner, and competing quotations before review. A software request could additionally route to IT for security assessment, while procurement retains responsibility for supplier suitability and purchasing terms.

Language-model tasks would be limited to interpreting submissions, extracting candidate fields, and explaining relevant policy passages. Server-side rules would validate amounts, determine approvers, and enforce permitted state transitions. This separation keeps uncertain interpretation away from authorization logic and makes it possible to test the approval process independently of model output.

Each request would move through explicit states such as draft, clarification, review, approved, and handed off. Material edits would invalidate affected approvals according to agreed rules. Timeouts could notify delegates, but would never convert silence into approval. Missing evidence, conflicting instructions, or failed authorization checks would stop the relevant action for human review.

Potential integrations include SAP Ariba, Coupa, or Microsoft Dynamics 365 for procurement records, and Microsoft Teams or Slack for review notifications. These are proposed development options, not existing working connections. Feasibility depends on your subscriptions, API availability, sandbox access, permission scopes, and the operations each provider allows in your environment.

Implementation would begin with documented field mappings and read-only validation where practical. Approved write operations would require scoped credentials, duplicate-prevention controls, and reconciliation of returned identifiers. If a provider times out after receiving a request, the system would check the external record before retrying rather than assume that the first attempt failed.

DOD IT Solutions can scope the application for hosted SaaS or a client-server installation within your chosen infrastructure. The design would specify organization boundaries, backup responsibilities, network connectivity, and operational access. Hosting arrangements are selected during discovery, with separate development, testing, and production environments where required by the agreed operating model.

A client-server deployment can keep application records on client-controlled infrastructure, but external model calls may still transmit selected content. The architecture review would therefore address inference location, document extraction services, outbound traffic, and residency requirements together. Capacity planning would use expected document volumes and concurrent reviews rather than assume unlimited processing or fixed response times.

Approved purchasing policies, category definitions, and delegation matrices would form a versioned knowledge collection. Retrieval would filter documents by user permission, organizational entity, and effective date before providing context to the model. Reviewers would see supporting passages so they can distinguish a documented requirement from an uncertain interpretation or missing policy coverage.

Adaptation would start with extraction schemas, controlled prompts, and examples authorized by your team. Corrections would enter a reviewed evaluation set rather than automatically change production behavior. Optional fine-tuning would require a separate justification and data review, while model changes would be tested against ambiguous quotations, outdated policies, and attempts to manipulate agent instructions.

The security design would enforce role-based access, entity separation, and server-side checks for every consequential operation. Requesters should not approve their own spending unless an explicitly approved policy permits it. Credentials would be stored in a secrets service, and external tools would receive only the permissions required for their agreed responsibilities.

Uploaded quotations and retrieved documents would be treated as untrusted content that cannot alter tool permissions or approval requirements. Audit records would capture relevant inputs, document versions, reviewer actions, and connector outcomes without unnecessarily retaining sensitive model prompts. Retention, deletion, backup access, and incident procedures would be documented with the client's designated security owners.

The engagement includes full source code for the custom application, implemented connector code, database migrations, deployment configuration, and agreed automated tests. Handover materials would describe approval rules, document ingestion, model configuration, and administrative tasks. Third-party services, libraries, and model weights are not transferred as proprietary client assets and remain subject to their applicable licenses.

Acceptance would use representative requests and explicitly difficult cases, including missing quotations, incorrect approval limits, expired delegation, and interrupted handoffs. The project would also document known limitations and unresolved dependencies. Administrator walkthroughs and operational runbooks support ownership after deployment; any ongoing maintenance, additional connectors, or expanded workflows would be defined through a separate agreed scope.