How One Research Firm Cut Trend Reports to 35 Min With AI

A market intelligence platform's analysts reacted to client questions. AI research agents now scan the web and judge what matters — decision-ready reports in under 35 minutes for $3.

35 min

Delivers a decision-ready report

Implementation Time

Chris Taylor

CEO & Co-Founder

Fractional AI

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The Challenge

The platform traditionally relied on senior analysts responding reactively to client questions. There was no scalable mechanism to proactively identify emerging signals — internet trends, consumer sentiment, behavioral shifts — that typically precede measurable sales changes.

What They Built

Fractional AI built a modular research-agent system that mimics experienced analyst workflows in two stages: topic generation, where agents scan public web data to surface emerging trends for specific brands or categories, and structured evaluation, where affirmative and negative agents debate a trend's importance using sales data and external evidence while a third agent simulating a brand executive renders the final decision.

The system uses composable agent loops (topic generation, proposition evaluation, debate orchestration, stakeholder simulation) built on the OpenAI Agent SDK with the o4-mini model. Streamlit supported prototyping and FastAPI runs production, with Braintrust for evaluation. Research was deliberately separated from judgment to reduce bias — research agents gather evidence while the judge reviews briefs without independent tool access.

AI Role

The system mimics an analyst team. Topic-generation agents scan public web data to surface candidate trends. In evaluation, an affirmative and a negative agent debate each trend's importance using sales data and external evidence, and a third agent simulating a brand executive issues the final verdict. Research and judgment are deliberately separated so the judge reviews briefs without its own tool access, reducing bias.

AI Model

OpenAI Agent SDK, o4-mini, Streamlit (prototyping), FastAPI (production), Braintrust (evaluation)

Infrastructure

FastAPI in production (Streamlit for prototyping) • OpenAI Agent SDK for agent orchestration • Braintrust for evaluation • Public web data and client sales data as evidence sources

Integration Points

Composable agent loops for topic generation, proposition evaluation, debate orchestration, and stakeholder simulation • Research separated from judgment — judge reviews briefs without independent tool access • Public web scanning and sales-data lookups feeding the debate

Impact

Reports in under 35 minutes

Delivers decision-ready reports in under 35 minutes (typically 25-35 minutes).

~$3 per report

Each report costs approximately $3 to produce.

~80% verdict consistency

About 80% of report pairs reached the same verdict on re-run.

Technology Utilized

Implementation Complexity

Time Savings

Cost Reduction

Best Fit For

Best fit for market-intelligence or research businesses that want to shift from reactive analyst work to proactive, low-cost, scalable trend discovery.

Chris Taylor

CEO & Co-Founder

Fractional AI

CEO & Co-Founder of Fractional AI, helping PE firms and portfolio companies implement AI workflow automations, product features, and diligence at scale.

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Industry:

Professional Services

Business Function:

Operations

Company Size:

Project Cost:

Cost not disclosed

Ownership:

Private Equity-Backed

Organization Type:

Private Company

AI Pattern:

Data Synthesis & Reporting

Decision Support & Scoring

Value Type:

Time Savings

Cost Reduction

AI Model:

Frequently Asked Questions

How did a market intelligence platform produce trend reports in under 35 minutes?

By replacing reactive analyst research with a modular AI research-agent system. Topic-generation agents scan public web data for emerging trends, then affirmative and negative agents debate each trend's importance while an agent simulating a brand executive decides - producing decision-ready reports in under 35 minutes.

What AI models and tools power the trend-discovery agents?

The system uses composable agent loops built on the OpenAI Agent SDK with the o4-mini model. Streamlit supported prototyping, FastAPI runs the production system, and Braintrust is used for evaluation.

What results did the market intelligence platform achieve?

The system delivers decision-ready reports in under 35 minutes (typically 25-35), each costing approximately $3 to produce, with about 80% of report pairs reaching the same verdict on re-run.

How long does it take to generate a trend report?

Typically 25 to 35 minutes per decision-ready report. A separate project implementation timeline was not disclosed.

Who is this AI trend-discovery approach best for?

It is best suited to market-intelligence or research businesses that want to shift from reactive analyst work to proactive, low-cost, scalable trend discovery.