Behavioral Intelligence for Modern Communication. Dissect is built to decode behavior within communication — not just the message, but what the message reveals. A one-word reply means nothing until you know who sent it. Dissect is designed to read each signal against that person’s own baseline, in context and over time.
No form. No upload required to begin. The user opens a conversation and describes the situation in plain language. Dissect starts reading behavior from the first message. Upload evidence to sharpen it. Keep talking to go deeper. The session is a conversation — not a submission.
Open a conversation. Describe the situation in plain language. No upload required. Dissect begins behavioral analysis immediately from what you describe. Chat is the primary interface.
Upload screenshots, texts, emails, voice notes, video, or journals. Uploads are the evidence layer — they sharpen the analysis that chat already started. Confidence moves from Moderate to High.
Structured behavioral output. ABCD scores. Red and green flags. Reciprocity classification. Contradiction index. Risk profile. Predictor forecast. Every session builds the behavioral picture.
Finance has Bloomberg. Health has Epic. Sales has Gong. Existing tools generate, rewrite, coach, or summarize communication. None of them analyze the behavior within it across time, context, and relationship history — then measure shifts against a user's own baseline. Every channel where humans communicate and misinterpret each other — text, email, Slack, screenshots, voice notes, social media — that behavioral data has never been decoded at scale. That is the white space. That is Dissect.
Bloomberg. Real-time market intelligence built on financial signal data. A $6B company. The category did not exist before it was named.
Epic. Clinical behavioral data infrastructure for healthcare systems. Built on the argument that structured health data creates compounding institutional value.
Gong. Communication pattern analysis for revenue teams. Built on recording and transcribing human conversations to surface behavioral signals at scale.
Modern communication is also visual. A single emoji, acronym, reaction, or "K." can carry tone, context, and emotional weight. Abstract Decoder interprets those markers when they appear — not on every message.
For the first time in history, large volumes of everyday communication are produced by machines. People can no longer trust that what they receive is human. The need to decode authenticity and intent has never been greater.
Lost relationships, failed hires, broken partnerships, missed deal signals. The cost of misreading behavior is no longer abstract — it's a recurring, quantifiable problem across every industry and relationship type.
Persistent memory alone is not Dissect’s differentiation. Dissect is designed to compare communication against per-relationship, per-context baselines and track drift across time. The method organizes evidence around Affect, Behavior, Cognition and Direction.
Consumer Social is the entry point — social interactions, careers and networking. Dissect Social is designed to include a dedicated mode for neurodivergent users: a real-time guide for social and networking environments that surfaces ice breakers, conversation starters, and interaction cues calibrated to how that user actually communicates. The expansion beyond consumer reaches every domain where behavioral misreading has a measurable cost. Governments. Institutions. Organizations. Global enterprises navigating cross-cultural intelligence, AI transparency, and behavioral risk at scale. The behavioral intelligence layer does not stop at the personal. It scales to every environment where humans communicate and decisions depend on what behavior actually reveals.
Every session makes Dissect smarter about that specific relationship. The 90-day behavioral baseline takes 90 days to build — per relationship, per user. Any competitor starting today starts that clock from zero. The lead does not just hold. It widens.
Each person profile is designed to retain structured analysis for an ongoing engagement and its context. Subsequent sessions compare new signals against documented history, subject to the user’s retention and deletion choices.
Designed to identify recurring communication patterns and drift against that person’s baseline in the relevant context. Predictor forecasts require sufficient session history and evidence.
When symbols and visual cues replace nonverbal communication, Dissect reads it anyway. Emojis, reaction-only messages, punctuation shifts, memes, and acronyms carry behavioral signal. Abstract Decoder activates on compressed and symbolic communication — extracting intent from what was never written in words.
The proprietary asset is not the model — it is the accumulated behavioral dataset each user builds. Cancel and it is gone. That is not a retention tactic. That is what the product actually is.
Social. Office. Global. Civic. Date. Each environment uses the same analysis engine with different behavioral norm baselines. The context calibration changes how signals are weighted — not how they are extracted.
Build is underway with a technology partner capable of delivering the platform — iOS-first architecture, AI integration, and backend infrastructure. This arrangement may evolve as a dedicated technical co-founder comes on, a priority hire from this raise.
Dissect started with a question that no app could answer. Not the message — the behavior behind it. That question led to years of documenting and memorizing the nuances that surface when communication becomes ambiguous.
The same pattern exists across every human environment — dating, business, networking, professional relationships. People aren't struggling to communicate. They are struggling to interpret behavior within communication. That gap became Dissect.
Kianga J. Moore spent years conducting high-stakes interviews with influential people and working in fast-paced communication environments where unspoken rules, hidden meaning, and attempts to find the truth in ambiguity. That practice became the methodology for Dissect. She is a former Broadway publicist, Pulitzer Center AI Accountability Network member, invited FII media delegate, and member of the Innovation Alliance of Michigan.
At the heart of Dissect is a simple belief: when people better understand the intent behind communication and behavior, we get better at being human. The product is built to reduce guessing, improve interactions and help people connect with more clarity.
This is the public Dissect website. The animated example illustrates the product concept. Do not submit private conversations or sensitive information through the inquiry form.
The website collects the contact details you choose to submit for waitlist updates or investor inquiries. Submissions are stored in the site’s Cloudflare database for founder review.
Use the investor inquiry form to request access to or deletion of website contact information. App-level export, deletion and security controls require separate implementation and testing.
Your behavioral data is never sold to third parties, never shared with advertisers, and never used to train models outside your own profile.
Dissect’s prototype has been tested with 500+ organic users. Investors and strategic partners can request further information or a conversation with founder Kianga J. Moore. The technical co-founder position is open.
Dissect launches on iOS first. Be first in line.
The answers are direct. The methodology is proprietary. The deck is available under NDA.