R&D Journal - Rose Agentic Platform

This journal documents the Research & Development work performed on Rose, an agentic platform for inbound marketing - a new category in the B2B marketing technology space.

Rose combines RAG (Retrieval-Augmented Generation), multi-agent orchestration, and B2B visitor intelligence to automate inbound marketing conversations.

Purpose

Document technical challenges, hypotheses tested, failures, and solutions developed as part of Rose's experimental development.

Methodology

Each R&D entry follows a structured approach:

1. Context: Business situation and active clients
2. Technical Challenge: Problem statement and state of the art
3. Hypothesis: Testable assumption
4. Development Work: Implementation details
5. Testing & Validation: Method and metrics
6. Results: Measured outcomes
7. Conclusion: SUCCESS / PARTIAL SUCCESS / FAILURE

Key Business Metrics

All hypotheses validated against three core metrics:

1. Initial Engagement Rate: % of visitors who interact with widget
2. Conversation Depth: Average number of turns per conversation
3. Conversion Rate: % of conversations leading to demo/email capture

Journal by Year

2026

Second year of R&D - Adaptive multi-tenant conversation orchestration, compounding context, and closed-loop agent evaluation.

• Q1: Literature review on multi-agent orchestration strategies, skill systems vs dedicated agents, and context reduction
• Q2: Context-engine expansion, experiment marts, productized website scraping, and relay-managed agent evaluation workflows

See 2026 R&D Journal for detailed entries.

2025

First year of R&D - Foundation through multi-agent architecture.

• Q3: Platform foundation, LightRAG, multi-tenant storage
• Q4: Visitor intelligence, enrichment pipeline, interest signals

See 2025 R&D Journal for detailed entries and measured impact.