TECH
Under the hood

The engine that

answers the only

question that matters.

Six AI layers. Fourteen data sources. One answer: will users pay? Here's exactly how Boffo works.

Architecture

Six layers of intelligence.

Layer 01

Fine-Tuned LLMs

We train domain-specific language models on a corpus of successful and failed startup post-mortems, VC investment memos, and Y Combinator batch data. These models understand founder-market fit, business model viability, and market timing at a level generic LLMs cannot match.

GPT-4o fine-tuneCustom RLHFLoRA adaptersSynthetic data pipeline
Layer 02

RAG + Vector Search

Retrieval-Augmented Generation grounds every analysis in real, current data. We embed and index 50,000+ VC deal records, funding announcements, competitor analyses, and market reports into a high-performance vector store. Every query retrieves the most relevant context before generation.

PineconeOpenAI EmbeddingsHybrid searchReal-time indexing
Layer 03

Context Engineering

Raw ideas are restructured through our proprietary context engineering pipeline before hitting inference. We extract entities, map competitive landscapes, identify ICP (Ideal Customer Profile), and format the submission into a structured prompt that maximizes model precision.

Entity extractionOntology mappingICP classificationPrompt chaining
Layer 04

VC Metrics Engine

Our scoring engine evaluates 23 distinct VC metrics: TAM/SAM/SOM sizing, competitive moat depth, revenue model viability, founder-market fit signals, network effects potential, and more. Each is scored against benchmarks derived from funded vs. unfunded startup data.

23 VC metricsBenchmark scoringConfidence intervalsComparative ranking
Layer 05

Rapid Prototyping Engine

Once the viability report is generated, our system auto-builds a functional prototype of the product concept. Using component libraries and AI-generated UI flows, we create interactive mockups that accurately represent the core value proposition.

AI UI generationComponent synthesisUser flow mappingInteractive delivery
Layer 06

Demand Testing & WTP

The prototype is deployed to curated user panels matching the target ICP. We measure behavioral signals: time-on-task, feature engagement, conversion on simulated payment walls, and exit intent. This produces a Willingness-to-Pay (WTP) score — the only signal VCs actually care about.

Behavioral analyticsWTP modelingICP panel targetingReal payment intent
Data Sources

Fourteen authoritative sources.

Crunchbase

Global VC deal database, funding rounds, valuations

Y Combinator

Batch company data, pivots, success patterns

Product Hunt

Consumer traction signals, launch resonance metrics

AngelList

Early-stage deal flow and investor behavior data

CB Insights

Market maps, sector trends, emerging technology signals

PitchBook

Private market valuations and investor portfolio analysis

SEC EDGAR

Regulatory filings, S-1 benchmarks for comparables

LinkedIn Talent

Team composition signals and talent density metrics

App Store / Play

Consumer app traction, review sentiment, retention proxy

G2 / Capterra

B2B software reviews, NPS proxy, competitive switching signals

SimilarWeb

Web traffic patterns, channel mix, audience overlap

Semrush

Keyword intent data, SEO opportunity sizing

USPTO Patents

IP landscape mapping, defensibility signals

Academic Research

Peer-reviewed market studies and behavioral economics data

Put the engine to work.

Submit your idea and see all six layers produce a full demand analysis in under 48 hours.