Project MonetRequest demo
Home/Blog/Frigade Assist API: Pricing, Features & How It Works

Automation · Project Monet Briefing

Frigade Assist API: Product-Grounded AI Agents Explained

Frigade Assist API lets an existing AI agent call Frigade as a specialized product-knowledge tool instead of replacing the agent's model or orchestration.

Published 2026-09-09 · Updated 2026-09-09 · By Project Monet Editorial Team

Frigade Assist API connecting an existing AI agent to live product knowledge and in-product guidance

01

What Frigade launched

Frigade launched Assist API on September 8, 2026 for teams that already have an AI agent. The existing agent keeps its model, prompts and conversation logic, while Frigade is exposed as a callable tool for product-specific answers and in-product guidance.

Frigade says its product-learning layer uses the software itself, not only static help-center text, and can relearn workflows after product changes. That relearning behavior is a vendor claim rather than an independently benchmarked accuracy guarantee.

02

How the integration works

Frigade's current public example uses the Vercel AI SDK: the application's model decides when to invoke a Frigade guidance tool, then calls frigade.assist with the user and intent. Frigade says the approach is framework-agnostic for agents that support tool calling.

This makes Assist API a product-expertise layer, not the general reasoning model for every message. Questions about the application UI, settings and multi-step workflows are the clearest fit; generic reasoning can remain with the existing agent.

03

Pricing and security

Frigade's current pricing page lists Growth starting at $1,000 per month, including five seats, two agents and 2,500 queries, with Enterprise priced separately. API access is listed on Growth and Enterprise, so teams should recheck current allowances before budgeting.

Frigade documents SOC 2 Type II, GDPR compliance, TLS 1.2+ in transit, AES-256 at rest, PII scrubbing and enterprise options such as self-hosting and EU data residency. These are vendor-documented controls; regulated teams should still verify the current security package and data flows.

04

What is still unproven

Public third-party evidence comparing Frigade's answer accuracy, workflow completion and relearning reliability is still limited. The launch material also does not justify inventing a universal latency SLA, undocumented rate limit or model-provider claim.

For the implementation path, read How to Add Frigade Assist API to an Existing AI Agent. The useful test is whether guidance stays correct across real product releases, roles and permission boundaries.

Sources

Primary and supporting sources

Facts were rechecked against the linked sources immediately before publication. Pricing, product availability and rollout status can change.

Project Monet

Useful signals. Clear decisions. Better digital work.

Project Monet turns relevant shifts in AI, creator tools and the web into practical context—and builds focused websites for businesses ready to grow.

Request a free homepage concept