---
title: "Agents · Research & Competitive Intelligence · Marxen"
url: "https://marxen.in/cloud/agents/iv"
description: "Agents that read, synthesise and surface insight from large and fragmented knowledge estates."
---

# Research & Competitive Intelligence

*[Agents](https://marxen.in/cloud/agents) · Section IV*

Agents that read, synthesise and surface insight from large and fragmented knowledge estates.

## 15 · Research Intelligence Assistant

*Research · In build*

**The problem**
A firm holds thousands of long-form research reports. Nobody reads twenty pages to answer one question, so the back catalogue sits unused while the firm pays to produce more of it.

**What it does**
A conversational layer over the entire research estate. Users ask and get a grounded answer with citations back to the source report.

**What changes**
Time to insight collapses from reading a report to asking a question. The archive becomes an asset instead of storage.

## 16 · Competitor Watch Agent

*Market intelligence · In build*

**The problem**
Competitive intelligence means analysts searching multiple sources by hand and compiling updates on a cycle. Hours per analyst, and the monitoring is only as consistent as the analyst's week.

**What it does**
Automates competitor research across sources and assembles a consistent intelligence report on a fixed cadence.

**What changes**
Research hours per cycle drop sharply and the reporting becomes uniform, which is what makes it comparable period to period.

## 17 · Decision Intelligence Agent

*Consulting · In build*

**The problem**
Subject-matter experts search large file stores of documents and spreadsheets to answer internal and customer queries. As volume grows, turnaround slows and the team caps how many requests it accepts.

**What it does**
A sensing layer over fragmented internal knowledge, letting experts and executives research and reach informed decisions in near real time.

**What changes**
Query resolution moves from days to near-immediate, and the expert team's ceiling on request volume lifts.

## 18 · Deal Origination & One-Pager Agent

*Document automation · In build*

**The problem**
A deal-origination team compiles a hundred-plus company profiles a month from eight to ten fragmented sources. Each profile can take a full working day, leaving little bandwidth for the evaluation the team actually exists to do.

**What it does**
Automates the research, enriches across sources with enforced source prioritisation, and generates a structured one-pager. Fragmented tools consolidate into one system of record.

**What changes**
Per-profile time falls dramatically, data quality improves because source hierarchy is enforced rather than remembered, and leadership queries resolve in seconds.

## 19 · Media Planning Intelligence Dashboard

*Media planning · In build*

**The problem**
Planners interpret audience data across several sources by hand. Cycles are slow, outputs differ between planners, and cultural insight rarely survives the journey into activation-ready strategy.

**What it does**
A decision-intelligence agent and dashboard that standardises how audience data becomes activation-ready media strategy, with consistent decision logic across the planning team.

**What changes**
Planning cycles shorten, subjective variation between planners drops, and insight arrives in a form the activation team can act on.

## 20 · Case-Study Discovery Agent

*Research intelligence · In build*

**The problem**
Research, advisory and strategy teams need to explore a large estate of case studies conversationally, with directional answers and structured narratives, rather than searching datasets by hand.

**What it does**
Delivers grounded answers, structured strategic narratives and case-level exploration across the case-study estate.

**What changes**
Exploration becomes a conversation. Findings that previously required knowing what to search for now surface by asking.

## 21 · Analyst Database Agent

*Research · In build*

**The problem**
Building and maintaining an analyst contact database means manual research across websites and professional networks, and the database is stale within a quarter.

**What it does**
Researches and assembles analyst contact records automatically, keeping the outreach database complete and current, and generating event lists on demand.

**What changes**
Manual search time falls and the database stops decaying between refreshes.

## 22 · Research Synthesis Agent

*Research · In build*

**The problem**
Analysts extract insight from source documents and turn it into presentation-ready summaries by hand. Significant time per deliverable, capping how many requests fit inside standard turnaround.

**What it does**
Extracts insight from source material and assembles presentation-ready summaries, so the analyst starts from a draft rather than a blank document.

**What changes**
Throughput rises within the same turnaround window, and analyst effort redirects toward analysis rather than formatting.

## 23 · Synthetic Focus Group Agent

*Research · In build*

**The problem**
Persona development and concept testing depend on recruitment, moderation and scheduling. Weeks pass before a team learns something it needed before the creative was made.

**What it does**
Generates research-grounded synthetic consumers from segmented research and first-party data, then runs simulated focus group discussions for directional response on creative and messaging.

**What changes**
Persona creation and early-stage testing move from weeks to hours, with traditional research reserved for the decisions that genuinely need it.

**Honest framing**
The output is directional. It replaces the third round of concept testing, and it will not stand in for a study you would defend to a board.

## 24 · Competitive Intelligence Reporting Agent

*Competitive intelligence · In build*

**The problem**
Competitor reporting is manual, inconsistent and dependent on fragmented sources, so the insight is out of date by the time it is circulated.

**What it does**
Automates competitor intelligence end to end, gathering across review platforms, professional networks and company pages, and producing a consistent report on a set cadence.

**What changes**
Manual effort drops substantially and reporting arrives on time and in the same shape every period.

## 25 · Media Planning Research Agent

*Media planning · In build*

**The problem**
Planners and strategists analyse fragmented data from multiple third-party research sources, spending significant time synthesising it into something a plan can be built on.

**What it does**
Generates contextual research insight across multiple sources on demand, producing planning-ready summaries from a prompt.

**What changes**
Analysis time falls and insight generation becomes consistent rather than dependent on which sources the planner happened to check.