Overview
A leading digital commerce platform needed to simplify one of the most demanding steps in the solution provider journey: preparing an offer for publication. The existing process required users to gather information from multiple sources, complete lengthy forms, and validate visual assets against strict requirements. Nextant designed and delivered an AI-assisted workflow that transformed this fragmented process into a guided, scalable experience. The result was a smarter publication journey that reduced manual effort, improved submission quality, and helped solution providers move forward with greater confidence.
Challenge
For solution providers, preparing offers for publication required significant manual effort, cross-checking, and rework. The process created friction at multiple points:
- Fragmented information gathering: Solution providers needed to complete more than 50 submission fields using content scattered across product websites, technical documentation, sales collateral, and supporting materials.
- High-effort submission preparation: The time and complexity required to complete submissions slowed publication cycles and increased the risk of abandoned offers.
- Asset readiness and compliance gaps: Logos and media assets often failed marketplace requirements because of incorrect file formats, resolutions, dimensions, or safety issues, creating additional review cycles and delays.
- Inconsistent submission quality: Because users interpreted field requirements differently, submissions varied in completeness, tone, and readiness for review.
The platform needed more than automation. It needed a practical AI solution that could interpret unstructured information, support human decision-making, improve content quality, and fit securely into an enterprise-grade technology environment.
Solution
Nextant designed and built a guided, AI-assisted publishing workflow that helps solution providers move from unstructured source information to publication-ready content and compliant visual assets.
The experience guides users through four connected stages: identifying the appropriate offer type, confirming the recommendation, generating and refining submission content, and validating visual assets against marketplace requirements. At each stage, users can review, approve, or adjust the AI-generated output, ensuring they remain in control throughout the publishing process.
Behind this guided experience, Nextant implemented a staged multi-agent architecture in which specialized AI assistants perform distinct tasks across the workflow. Separate assistants handle offer classification, content generation, quality review, and asset validation, with each stage using the outputs from the previous step.
This modular approach improves traceability, reduces the risk of incomplete or inconsistent submissions, and makes it easier to refine individual parts of the workflow as marketplace requirements evolve. It also allows the solution to combine automation with human oversight, supporting greater speed and consistency without removing provider judgment from key decisions.
How the Publishing Workflow Works
- Offer Classification: The workflow analyzes product webpages, technical documentation, supporting links, and marketing collateral to recommend the most appropriate offer type, such as SaaS, Virtual Machine, or Container. This gives solution providers a more consistent starting point and reduces ambiguity early in the submission process.
- Provider Confirmation: Before content generation begins, the solution provider reviews and confirms the recommended classification. This human-in-the-loop checkpoint ensures the workflow reflects the provider’s intent and creates transparency around AI-generated decisions.
- Field Generation and Content Review: Once the classification is approved, the publishing assistants generate draft content for key submission fields using the available source materials. A separate review step evaluates the content for completeness, consistency, clarity, and alignment with publication requirements before presenting it to the user for approval.
- Asset Validation and Optimization: The asset workflow checks logos and media files for technical requirements such as format, resolution, and dimensions, as well as applicable content-safety requirements. It can generate compliant logo variants and suggested alt text, helping providers prepare assets for publication and reduce avoidable review cycles.
Together, these capabilities create a guided publishing experience that reduces repetitive work, improves submission consistency, and helps solution providers prepare offers with greater confidence.
Technology Used
- AI and reasoning: Azure AI Foundry and a multi-agent architecture to orchestrate classification, content generation, review, and optimization.
- Data extraction and validation: Custom Playwright scraper, Azure AI Document Intelligence, and Azure AI Content Safety to gather, interpret, and validate source information and assets.
- Cloud platform and delivery: Azure Container Apps, Python, FastAPI, Azure Blob Storage, and Microsoft Azure security and compliance standards to support scalable, secure implementation.
