UnfakeIT

Quick Facts

Tech Stack

AI / ML

Anthropic

Backend

Node.jsExpress

Database

PostgreSQL

Frontend

ReactTypeScript

Infrastructure

RailwayVercel

About the Business

UnfakeIT is a validated conversation quality methodology for AI chat and voice agents. It sits between the upstream LLM (Claude, GPT, Gemini) and the customer, applying judgment behaviors the raw model doesn't do consistently. The asset is the methodology itself — not a SaaS business. It's IP, validation, and productization work, packaged as a deployable framework. WHAT IT FIXES: Standard AI customer service handles informational questions reasonably but fails at specific moments: - Repeat queries get scripted answers instead of acknowledgment - Frustrated customers get stranded by escalation theater - Multi-turn conversations lose confidence calibration - Dead-end handoffs abandon customers when they need help most UnfakeIT addresses these specific failure modes with documented behavioral rules and audit tokens that fire at the right moments. WHAT'S INCLUDED: - 6,462-line system prompt specification (the methodology core) - 119 documented audit tokens with FIRES WHEN / NOT FIRES / EVIDENCE rules - 39 validated scenarios covering judgment behaviors, escalation handling, repeat queries, severity inference, and tenant-authorized commitments - 117 API calls at 100% pass rate on Claude Sonnet 4.6 - Deployed landing page at unfakeit.app - Live demo at unfakeit.app/demo (real backend, real audit tokens, real cost metadata) - Commercial single-organization license framework - The brand "UnfakeIT" and domain unfakeit.app - Full documentation and integration notes WHO BUYS THIS: - AI agencies building voice/chat products for SMBs (license once, deploy across all client accounts) - Wrapper platforms (Vapi-based, Retell-based, Synthflow-style) wanting conversation quality differentiation from competitors - Operators with an existing AI agent customer base who want to add a humanization tier - Anyone in AI customer service who values reaching the market with a validated artifact faster than 7 months of in-house research VALIDATION: The 39 scenarios cover the specific behaviors the methodology addresses. Each behavior has documented trigger conditions, expected outputs, and audit tokens that fire when applied. The validation suite runs against Claude Sonnet 4.6 with prompt caching enabled. WHY I'M SELLING: Solo founder in Bengaluru. Built this over 7 months out of personal frustration with how robotic AI customer service has become. The methodology is fully validated and deployable. Direct sales isn't my strength and my primary venture is a different project. Selling so the methodology ships rather than sits. VALUATION CONTEXT: Comparable in-house research effort would cost $50K-$100K in engineering time. Pre-revenue, so the asking reflects validation work and productization, not revenue multiple. Open to offers in the $3,000-$5,000 range.

Business Model

One-time commercial license sale. The buyer acquires the full methodology, audit framework, validated scenarios, brand, and domain as a single transaction. Post-acquisition, the buyer can monetize through any of these models: - License the layer to AI agencies and wrapper platforms at $999-$2,999 per organization (founding-10 mechanic available) - Integrate the layer into an existing AI agent product as a quality differentiator - White-label the methodology and resell to end-customers - Deploy as a managed service for SMBs running AI chat/voice agents The commercial single-organization license framework is already drafted and ready to use.

Competitive Landscape

Direct competitors (enterprise CX platforms with similar outcome class): - Sierra (AI agent platform, well-funded, enterprise-focused) - Intercom Fin (resolution-based AI customer support) - Decagon (AI customer support at enterprise scale) - Ada (enterprise conversational AI) These compete on resolution-grade conversation behavior but at enterprise pricing ($50K-$500K+ contracts) and enterprise integration complexity. UnfakeIT differentiates by: - Offering the same outcome class at SMB pricing - Being a layer, not a platform (works with any upstream LLM) - Pre-built validation and audit framework that buyers can verify before deploying - No multi-month integration project Indirect competitors (commodity humanization tools): - ElevenLabs voice modeling (TTS quality, not conversation behavior) - Hume AI (emotional inflection, not judgment layer) - Prompt engineering frameworks (DIY, not productized) These solve different parts of the problem. UnfakeIT focuses specifically on the conversation behavior layer, not voice quality or emotional inflection.

Reason for Selling

Solo founder building a different primary venture that needs capital and focus. UnfakeIT is a complete side project that I built out of personal frustration with how robotic AI customer service has become. The methodology is fully validated and deployable. The work is done. Direct sales to AI agencies and wrapper platforms isn't my strength — I'm a builder, not a salesperson. Selling this asset to someone who has the network or platform to monetize it properly means it ships rather than sits. Proceeds fund my primary venture. The buyer gets a productized, validated framework that would take 6-12 months and $50K-$100K in engineering time to replicate.