ViBe://AUTOMATE

AI Research Analyst

Research work is time-consuming and often repetitive — monitoring competitors, aggregating market data, scanning industry news, and formatting findings into reports. An AI Research Analyst handles the gathering and formatting so your team focuses on interpretation and strategy.

What it handles

Research at scale, on schedule.

The AI Research Analyst connects to web sources, internal data systems, and your document management platform — running research cycles on defined schedules and delivering formatted reports.

  • Monitor competitor websites, press releases, and job postings for changes
  • Aggregate market data from configured public and licensed sources
  • Scan industry news and surface relevant developments on schedule
  • Generate structured research summaries in your approved report format
  • Compare current findings against previous runs and flag changes
  • Maintain a searchable archive of research outputs with version history

Systems it connects to

External and internal data sources.

Web search

Scans configured public sources — competitor sites, news feeds, industry databases.

Internal data

Connects to internal databases, CRM data, and document repositories.

Document management

Google Drive, SharePoint — saves reports, maintains version history.

How it runs

Scheduled runs and on-demand research.

ai-research-analyst — weekly-competitor-scan
TRIGGERMonday 6:00 AM — weekly competitor monitoring cycle
SCANCheck 12 competitor sites for pricing, feature, and content changes
DETECT2 changes found — Competitor A updated pricing page, B launched new feature
PULLCapture change details, archive previous state for comparison
AGGREGATECombine with internal sales data — win/loss vs. same competitors
DRAFTGenerate competitive update report using approved template
DELIVERSave to Drive + notify strategy team: "Weekly competitive update ready"

Human approval points

Interpretation and publication stay human.

  • Strategic conclusions and recommendations drawn from research findings
  • Any research report distributed externally to clients or partners
  • Research methodology changes — which sources to include or exclude
  • Findings used to inform public statements, press releases, or marketing
  • Interpretation of ambiguous or conflicting data points

Capacity recovered

Illustrative monthly time savings.

Monthly capacity recovered

~28 hrs

Illustrative estimate

Typical implementation time

2–4 wks

From kickoff to live

Automated research cycles

Weekly

Configurable cadence

Capacity estimates are illustrative. Actual hours recovered depend on the number of research tracks, source complexity, and report formatting requirements.

Implementation

Live in 2–4 weeks.

01

Discovery

Define research tracks — competitors, markets, topics — and identify current data sources.

02

Build

Configure data connections, report templates, monitoring schedules, and delivery channels.

03

Pilot

Run first research cycle. Review report quality and source coverage with your team.

04

Full rollout

Activate all research tracks. Establish review cadence and feedback loop for continuous improvement.

Security & data handling

Research data access, controlled and logged.

Source-scoped access

Web scanning is limited to configured, approved sources. Internal data access is scoped to designated databases and document folders.

No training on proprietary data

Internal data and research findings are never used to train models.

Archive with version history

All research outputs are versioned. Previous states of monitored sources are retained for comparison.

External report approval gate

Reports marked for external distribution are always queued for human review before delivery.

FAQ

Common questions.

How current is the data the AI Research Analyst pulls?+

Web-sourced data is pulled at the time of each research run. You configure the sources — public websites, news feeds, industry databases — and the refresh cadence. Real-time data requires appropriate API access.

Can it access internal data sources?+

Yes. We connect to internal databases, document repositories, and data warehouses as part of the integration setup. Internal data is combined with external sources in the configured report format.

Does the AI draw strategic conclusions?+

It synthesizes and summarizes — it does not make strategic recommendations. Conclusions, implications, and decisions based on the research always require human interpretation and approval before external publication.

What report formats can it produce?+

We configure output to match your current templates — Google Docs, Word, PowerPoint slides, or structured data exports. Reports are saved to your document management system with version tracking.

Get started

Build your AI Research Analyst.

Book a demo to walk through your current research workflows and get a scoped build plan with source configuration, report templates, and a go-live timeline.