All Case Studies

South Florida VC Intelligence Platform

MARTy

Unlocking central intelligence. First build, then buy.

23
Connected Data Sources
Including News, DuckDuckGo, Microsoft Graph, Slack, Fireflies, Gemini, Claude, and 4 Vectorize indexes.
1
AI Agent
Named MARTy.
1.8M+
Knowledge Records
Ingested, deduplicated, and embedded for instant retrieval.
The Full Story
System ArchitectureAI AgentRAGData Infrastructure

The Problem

A venture fund’s highest-value context was scattered across partner inboxes, calendars, Slack threads, meeting transcripts, documents, and market research.

Partners needed to ask, “What do we know about this company?” or “What changed in this deal?” and get a sourced answer without retracing every conversation. The CRM needed to reflect those conversations while protecting private information and keeping people in control of sensitive changes.

The Solution

We built MARTy: a private AI intelligence platform that brought the fund’s communications, documents, and deal context together through one conversational agent.

MARTy connected information across sources, mapped relationships between people and companies, and retrieved answers with citations. Governed CRM tools let the team act on that information, with access controls and human oversight built into the system.

Email & CalendarSlack & MessagesMeeting TranscriptsDocs & AttachmentsCRM DataNews & Web ContextKnowledge SyncPattern RecognitionContext MappingSemantic AnalysisSecure FilteringConversational AgentCited AnswersDeal InsightsCRM UpdatesDocument GenerationContinuous Learning

Four months in, the question changed.

As we built MARTy, we were also watching existing AI products become more capable and more connected. Access to company knowledge across everyday tools was becoming a standard feature.

Meanwhile, the cost of developing and running a custom platform was growing. Features we were investing in were increasingly available through subscriptions.

After four months of building, we had to reassess whether continued custom development was the best use of the fund’s next dollar.

The Outcome

We prepared and delivered a product research proposal recommending existing AI tools that could provide similar core functionality more efficiently.

The proposal gave the firm a path to lower ongoing spending and greater flexibility as products evolved. It could benefit from new capabilities and integrations without funding every improvement to its own platform.

Building MARTy gave us a detailed understanding of the firm’s information, workflows, and requirements. That understanding informed our recommendation to pursue a different approach.

Our recommendation changed. The business problem we were there to solve stayed the same.

Where would AI make the biggest difference in your business?

We’ll help you understand the opportunity and choose the right approach, whether that means custom development, existing tools, or a combination.

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