From Lab to Market Shelf: Bringing Consumer & Market Intelligence to Microsoft Discovery

Integration Guide — Jun 3, 2026

Ground your scientific and material R&D in real-world market dynamics by connecting Fodda's curated knowledge graphs directly to Microsoft Discovery agent loops.

By Piers Fawkes · 4 min read

With the recent general availability of Microsoft Discovery and the preview of the local Microsoft Discovery App, the scientific community has gained a powerful agentic AI platform to automate the research and development (R&D) lifecycle.

By orchestrating specialized agent teams, researchers can navigate the cognitive loop from hypothesis generation to in-silico simulation and lab automation.

However, scientific breakthroughs do not happen in a vacuum. A new sustainable biopolymer, a grid-scale organic battery electrolyte, or a novel skincare active ingredient must eventually succeed in the real world. To be viable, R&D projects must align with:

• Consumer Trends: Is there active demand for this category?
• Market Economics: Are raw material prices, labor statistics, and supply chain indicators favorable?
• Traceable Evidence: Can we ground our assumptions in verified industry reports rather than generic predictions?

This is where Fodda bridges the gap. By exposing Fodda's curated consumer, retail, beauty, and macroeconomic knowledge graphs to Microsoft Discovery agent teams, organizations can build a closed-loop system that evaluates both physical feasibility and market viability simultaneously.

The Missing Link in R&D: Early Market Grounding

Typically, market analysis is treated as a separate phase that happens after a product is formulated. If a chemical formulation is too expensive to manufacture, or if consumer sentiment has shifted away from a specific packaging material, months of laboratory work can be wasted.

By integrating Fodda's API directly into a Microsoft Discovery agent loop, R&D teams can assign a specialized "Market Viability Agent" to work side-by-side with their "Synthesis" and "Simulation" agents.

Closed loop feedback: Fodda returns real-world market constraints back to the hypothesis generator, preventing wasteful physical lab trials.

How it Works: Equipping Discovery Agents with Fodda Tools

Microsoft Discovery allows developers to customize agent behavior by equipping them with domain-specific skills and external API tools.

We can expose Fodda's semantic search capabilities to a Discovery agent by declaring a Fodda Search tool. Below is an example configuration showing how a Fodda search tool can be structured inside a Microsoft Discovery Agent environment.

1. Define the Fodda Search Skill (SKILL.md / OpenAPI Schema)

In your agent's workspace, define the integration schema for the Fodda API to map search requests directly:

# Fodda Search Tool Definition for Microsoft Discovery
name: search_fodda_insights
description: "Search Fodda's knowledge graphs (retail, beauty, sports, ce-design) for consumer insights, industry trends, and macro signals."
parameters:
  type: object
  properties:
    graph_id:
      type: string
      description: "The targeted vertical graph, e.g., 'beauty', 'retail', 'sports'"
    query:
      type: string
      description: "Natural language query representing the trend or active ingredient, e.g., 'bakuchiol clean beauty trends'"
    use_semantic:
      type: boolean
      default: true
      description: "Whether to perform conceptual vector search (true) or exact keyword search (false)"
  required:
    - graph_id
    - query
      

2. Configure the Discovery Agent (AGENTS.md)

Instruct your Microsoft Discovery agent on when and how to leverage Fodda's intelligence layer during R&D loops:

# Market Viability Agent Instructions

You are the Market Viability analyst for the R&D team. Your role is to cross-reference every proposed chemical formulation or product concept with real-world consumer interest and economic signals.

## Guidelines
1. When the Hypothesis Generator proposes a formulation (e.g., a face serum using "Bakuchiol"), invoke `search_fodda_insights` on the `beauty` graph.
2. Search for consumer sentiment, commercial product launches, and growth metrics.
3. Query the Fodda Supplemental Data endpoint if you need matching macroeconomic metrics (e.g., consumer spending, raw material imports).
4. Synthesize the findings and flag any immediate market risks (e.g., declining interest, supply chain cost spikes) back to the lead orchestrator.
      

Concrete Scenarios: Lab to Market

Let's walk through how this agent coordination behaves in live research environments.

Scenario A: Skincare Ingredient R&D

A cosmetics lab is designing a sustainable anti-aging cream. The simulation agent suggests several retinol alternatives. The Market Viability Agent queries Fodda's Beauty Graph:

• Query: POST /v1/graphs/beauty/search with query "bakuchiol consumer demand and clean beauty sentiment"
• Result: Returns traceable evidence showing a 42% YoY increase in consumer queries for bakuchiol combined with positive sentiment around organic sourcing, confirming strong market pull.

Scenario B: Grid-Scale Battery Electrolytes

An energy lab is choosing between organic compounds for battery electrolytes. The Market Viability Agent queries Fodda's Supplemental Data Layer:

• Query: POST /v1/supplemental/context with sources ["FRED", "US_IMPORTS"] looking at "quinones raw material price index"
• Result: Pulls real-time import pricing data showing that one of the chemical precursors has spiked in cost, prompting the hypothesis engine to pivot to a more economically abundant alternative.

Get Started

Scientific research shouldn't wait until the manufacturing phase to discover that a product lacks a market. By bringing consumer intelligence directly into the early loops of the Microsoft Discovery Engine, teams can build commercially viable products from day one.

Are you running Microsoft Discovery or testing the Discovery App preview? Expose Fodda's knowledge graphs to your agent teams today.

Integrate Fodda into Microsoft Discovery

Contact our team to provision a free API Key and start grounding your scientific R&D workflows.

Piers Fawkes, Founder PSFK