AI Integration with Fonteva for Proposal Generation

The integration connects at Fonteva's Opportunity, Account, and Product/Price Book objects within Salesforce. An AI agent is triggered at key stages: when a new sponsorship Opportunity is created, when a prospect's engagement history is updated, or when a sales rep requests a draft. The agent pulls structured data (member tier, past event attendance, company size from the Account record) and unstructured context (notes from previous calls, email threads) to inform the proposal's narrative and pricing logic.

The core workflow uses the Fonteva CPQ engine for dynamic pricing but augments it with AI for narrative generation. For example, the agent can:

• Draft a custom executive summary that references the prospect's past sponsorship ROI or stated business goals.
• Recommend specific benefit packages (e.g., 'Thought Leadership' vs. 'Networking Focus') based on the prospect's firmographic profile and session attendance history.
• Generate personalized contract clauses, such as exclusivity terms or logo placement details, by pulling from approved clause libraries and matching them to the prospect's tier and package.
• Output a complete proposal document in a branded template, ready for review in Salesforce Files, reducing a multi-hour manual process to minutes.

Rollout is phased, starting with a human-in-the-loop approval step where sales managers review AI-generated drafts before sending. Governance is managed via Salesforce approval processes and audit logs that track which AI suggestions were accepted or edited. This controlled approach builds trust, ensures brand and compliance standards, and provides training data to refine the AI's output over time. The final architecture is a secure, event-driven system where the AI agent acts as a copilot within the existing Fonteva/Salesforce workflow, not a replacement.

The integration connects at three key points in the Fonteva/Salesforce stack: the Opportunity object for prospect context, the Product Catalog for pricing and benefits, and the Quote/Proposal generation workflow. An AI orchestration layer, typically deployed as a secure microservice, listens for events (e.g., a "Generate Proposal" button click in Fonteva) or scheduled triggers. It ingests structured data from the Opportunity's related Account, Contact, and past Engagement records, alongside unstructured data from notes or previous communications. This payload is enriched with approved marketing language, legal clauses from a connected Document Management system, and dynamic pricing rules from the CPQ engine.

The core AI agent uses a Retrieval-Augmented Generation (RAG) pattern. It queries a vector database containing past winning proposals, sponsor case studies, and benefit descriptions to retrieve the most relevant examples and clauses. A large language model then synthesizes a first draft, adhering to a strict prompt template that enforces brand voice, includes mandatory disclosures, and structures the proposal with sections like Executive Summary, Customized Benefits Package, Investment Tiers, and Terms & Conditions. The draft is automatically populated with the prospect's name, company, referenced past interactions, and calculated pricing, which is validated against the CPQ engine's rules for discounts and bundling.

For governance and rollout, the generated draft is not auto-published. It is routed to a Salesforce Approval Process or a dedicated review queue in Fonteva for the sponsorship sales manager. The system provides an audit trail showing which data sources and template clauses were used. A phased rollout typically starts with a pilot for a single sponsorship tier, using the AI as a "co-pilot" to accelerate first drafts by 60-70%, while maintaining human oversight for quality and relationship nuances. This architecture ensures the AI operates within the guardrails of existing CPQ logic and approval workflows, making it a force multiplier rather than a black-box replacement.

Implementation begins by mapping the AI workflow to Fonteva's data model and Salesforce CPQ objects. The core integration typically listens for a status change on a Proposal Request record or a custom button click within the Fonteva UI. It then triggers an AI agent that securely queries the related Account (sponsor prospect), Opportunity, Product (sponsorship packages), and historical Contract data. Using a structured prompt, the agent drafts a proposal narrative, dynamically inserts pricing from the CPQ quote (SBQQ__Quote__c), and pulls approved benefit language from a Fonteva Content library or Salesforce Knowledge. The final draft is attached to the record and logged in FeedItem for a full audit trail.

A phased rollout is critical for adoption and risk management. Phase 1 (Pilot) enables the AI agent for a single product manager or sponsorship sales lead, generating drafts in a dedicated Sandbox environment with a mandatory human-in-the-loop review step before any document is sent. Phase 2 (Controlled Expansion) introduces the workflow to the full sponsorship team, with the AI providing draft suggestions that populate a Proposal__c custom object for final edits and approvals within Fonteva's native approval processes. Phase 3 (Automation) connects the approved proposal to Fonteva's document generation and e-signature workflows, automating delivery while maintaining a governance checkpoint for any proposal exceeding a predefined discount threshold or containing non-standard terms.

Governance is enforced at the data, model, and process layers. All AI calls are routed through a secure gateway that enforces role-based access control (RBAC), ensuring agents only access Account and Opportunity data permitted by the user's Salesforce profile. Prompt templates and approved clause libraries are managed in a version-controlled repository, with changes requiring approval from legal and sponsorship leadership. Every AI-generated draft is watermarked and stored with metadata linking it to the source records, prompt version, and generating user, providing full lineage for compliance. This architecture ensures the AI acts as a controlled copilot within Fonteva's existing security model, accelerating deal cycles without introducing unbounded risk.