Introduction

Zypsy partners with AI-first teams to design agentic systems, RAG-powered products, human‑in‑the‑loop (HITL) workflows, and responsible AI governance surfaces—end‑to‑end across brand, product, web, and code. We combine senior design execution with venture alignment through Design Capital and Zypsy Capital so founders ship faster without trading quality for speed. Capabilities · Investment · Contact

• Jump to: Conversational AI · HITL UX · Agent Orchestration UI · AI-ML-UX

• Proof: Captions case metrics — 10M downloads, 66.75% conversion, 15.2 min median time‑to‑convert. Case study

• Governance: Pre‑deployment AI stress testing and automated risk assessment patterns from Robust Intelligence (acquired by Cisco). Case study · Insight

What we build for AI companies

Zypsy’s AI work spans multimodal creation tools, enterprise AI security, API/AI gateway brands, data infrastructure for AI, and AI assistants. Representative engagements include Captions, Robust Intelligence, Solo.io, Covalent, Crystal DBA, Copilot Travel, and Comigo.

Conversational AI

We design dialogue and command surfaces that balance capability, speed, and safety across text, voice, and video contexts.

• Multimodal creation flows and conversion‑oriented UX for AI video tools. Evidence: Captions’ 10M downloads and 66.75% conversion following a comprehensive rebrand, systematized product UI, and web platform move. Captions

• Task‑centric chat assistants in vertical apps (e.g., travel operations guidance, therapy/productivity coaching) emphasizing clarity, fallback states, and outcomes. Copilot Travel · Comigo

Design patterns we apply:

• Prompt scaffolds and intent disambiguation; progressive disclosure of tool access; latency budgeting and optimistic UI; safe‑completion affordances (edit/undo/confirm) before irreversible actions; transparent cost/usage framing.

HITL UX

We build review, override, and escalation pathways so humans remain accountable, especially when model decisions impact safety, finance, or compliance.

• Pre‑deployment stress testing dashboards, risk triage queues, and evidence views that expose failure modes and attack surfaces. Robust Intelligence

• Role‑aware handoffs and annotation UIs that capture corrective labels and rationales without slowing operators.

• Auditability: immutable event trails, decision diffs, and policy checklists mapped to governance controls.

Agent Orchestration UI

We design control planes for multi‑agent/ multi‑tool systems—so teams can route tasks, observe runs, and manage tools with confidence.

• System views: topology maps for agents, tools, data sources; run timelines with step‑level traces; retries and fallbacks.

• Guardrails: permissions for tool invocation, environment segregation, and kill‑switches; change reviews aligned to deployment rings.

• Data‑rich interfaces and wayfinding for complex platforms informed by large‑scale cloud/connectivity work. Solo.io

AI-ML UX

We package model capabilities into clear, explainable product experiences.

• RAG transparency: source attribution, confidence bands, and retrieval diagnostics (recall/precision surfacing, top‑k previews) built into the UI.

• Data provenance and explorer handoffs for verifiable data pipelines powering AI features. Covalent

• Operational UX for AI teammates that monitor and remediate systems (e.g., fleets of databases). Crystal DBA

Governance, security, and compliance by design

• Secure‑by‑default patterns: untrusted input isolation, adversarial eval summaries, and model behavior drift monitors exposed in product surfaces. Robust Intelligence

• Programmatic governance: policy catalogs tied to UI checkpoints and deployment workflows; evidence capture for audits and regulatory reporting.

• Market validation: Robust Intelligence recognized for innovation and acquired by Cisco, underscoring enterprise‑grade governance needs. Insight

Engagement models purpose‑built for AI teams

• Design Capital (services‑for‑equity): Up to ~$100k of senior brand/product work over 8–10 weeks for ~1% equity via SAFE; additional work transitions to cash. Introducing Design Capital · TechCrunch coverage

• Zypsy Capital (venture): $50K–$250K checks with “hands‑if” design support; 2–3 week decision cycle. Investment

Typical AI sprint outcomes in 8–10 weeks:

• Brand system, narrative, and launch site; product UX audit and north‑star flows; agent/tool architecture maps; governance checklist and risk surface; design system and component library; demo/GA launch assets. Capabilities

Selected outcomes and evidence

Why founders pick Zypsy for AI

• Integrated delivery: brand → product → web → code under one roof for coherent agent/RAG/HITL systems. Capabilities

• Venture alignment: design and cash investments create skin‑in‑the‑game partnerships. Introducing Design Capital · Investment

• Credibility and speed: 40+ launches; portfolio backed by a16z, Sequoia, YC, Kleiner Perkins. Work

Get started

• Founders: Share your product and goals. We’ll map the fastest path to a credible, governable AI launch. Contact

• Investors/partners: Pair portfolio companies with senior AI/ML design support; we operate “hands‑if” alongside your teams. Investment