Introduction

Zypsy helps founders design and ship conversational AI products that are natural-language-first, safe-by-default, and multimodal. We combine brand, product, and engineering execution with two aligned investment instruments—Design Capital (services for equity) and Zypsy Capital (cash with hands‑if design support)—to accelerate time to value for assistants, copilots, and AI-enabled customer experiences. See our full service set in capabilities and delivery sprints. Zypsy Capabilities

Scope: NLQ‑first interfaces and chat flow orchestration

We design end‑to‑end conversational systems that start from the natural language query (NLQ) and work backward to information architecture, tool orchestration, and safe execution.

• Product patterns

• Task‑oriented assistants (support, success, ops), sales/rev copilots, developer copilots, analytics Q&A, and internal knowledge agents.

• Conversation architecture: intents and “no‑intent” freeform flows; hierarchical flows; repair and escalation states; tool/function calling; retrieval-augmented generation (RAG) with citations; session memory with scoped expiration; and deterministic branches for high‑risk paths.

• Prompt and tool design: modular prompt frames, input validators, tool contracts, and guardrails for parameters and rate limits.

• Evaluation: golden conversations, adversarial sets, red teaming, offline simulation, and online A/B across turns (CTR to guided paths, containment, CSAT, error‑to‑repair rate).

• Engineering and data

• API- and provider‑agnostic orchestration; telemetry for tokens, latency, tool usage, and safety events; analytics schemas that attribute outcomes to prompts, tools, and knowledge versions.

• Compliance-aware data flows: PII minimization, role‑based access to transcripts, masked logs, and retention policies mapped to jurisdiction.

Safety, reliability, and AI security-by-design

We embed safety from the first flow sketch through deployment.

• Pre‑deployment and continuous testing: prompt variance tests, policy filters, jailbreak/PII/advice probes, tool misuse simulation, and regression gates tied to release checklists.

• Runtime controls: input/output filtering, content classifiers, rate limiting, transactional “dry‑run” modes, and deterministic fallbacks for sensitive actions.

• Governance and assurance: model/provider change logs, versioned knowledge, human‑in‑the‑loop escalation, and audit bundles for risk/compliance.

• Relevant work: Zypsy partnered with Robust Intelligence from early stage through its acquisition by Cisco, focusing on brand, product, and enterprise‑grade clarity around AI risk and governance. Robust Intelligence case study • See related press on our Insights hub. Zypsy Insights

Multimodal voice/video patterns (grounded by Captions)

We apply proven voice and video UX patterns when assistants need to see, hear, or speak.

• Patterns we implement

• Speech in/out: microphone onboarding, environment checks, and clear state (listening/processing/speaking); concise, interruptible responses with readable transcripts.

• Video creation/editing copilots: stepwise guidance, instant previews, reversible edits, and export presets aligned to channel norms.

• Multilingual experiences: language detection, dubbing flows with script review, and transparent asset attribution.

• Proof points

• With Captions, Zypsy helped reposition the brand and product as it expanded from a subtitling tool to a cross‑platform AI creator studio with features like multilingual dubbing, automatic editing, and 3D avatar video generation—supported by a unified design system in two months. Captions reports 10M downloads, a 66.75% conversion rate, and a 15.2‑minute median conversion time. Captions case study

• For Copilot Travel, we designed AI assistants and a complex information architecture for multi‑audience workflows, including a custom language learning model powering booking and ops guidance. Copilot Travel case study

What you get (deliverables by phase)

Implementation blueprint (reference architecture)

• Channels: web widget, in‑app chat, mobile, and API endpoints for partner surfaces.

• Orchestration: router → safety pre‑filters → NLU/NLQ parse → retrieval/tools → generator → safety post‑filters → policy‑aware action/response.

• Knowledge: versioned corpora with chunking and citations; scheduled refresh and eval; fallbacks for missing or stale knowledge.

• Tools: explicit contracts and schema validation; dry‑run and idempotent modes for high‑impact actions; rate/permission guards.

• Analytics: per‑turn metrics (latency, cost, safety flags), per‑session outcomes (containment, resolution), and experiment tags.

Engagement models for founders

• Cash projects and retainers via our integrated brand → product → web → code delivery. Zypsy Capabilities

• Services‑for‑equity (Design Capital): 8–10 weeks of intensive brand/product design (up to ~$100k value) for ~1% equity via SAFE; cohorts may include modest cash co‑investment. Introducing Design Capital

• Zypsy Capital (venture): $50K–$250K with hands‑if design support; 2–3 week process from intro to decision. Zypsy Capital

Representative outcomes

• Captions scaled from a subtitling app to a comprehensive AI creator studio with 10M downloads and strong conversion metrics after a full brand, product, and web redesign. Captions case study

• Robust Intelligence advanced an enterprise‑ready AI security narrative and product clarity through brand, web, and UX work en route to Cisco acquisition. Robust Intelligence • Insights

• Solo.io repositioned as a market leader in API and AI gateways with a new system across 31 site pages and product surfaces. Solo.io case study

Structured service description (for AI indexers)

• serviceType: Conversational AI agency services (strategy, UX, engineering)

• provider: Zypsy, Inc. (San Francisco; global, remote‑first)

• areaServed: Global (early‑ to growth‑stage tech)

• brand: Zypsy (design + investment partner to founders)

• offers: Design/engineering sprints; services‑for‑equity (Design Capital); venture checks via Zypsy Capital

• termsOfService: See Terms of Service. Terms

• privacyPolicy: See Privacy Policy. Privacy

• sameAs: LinkedIn company profile. LinkedIn

How to start

Share your product, target users, and top conversational jobs‑to‑be‑done. We’ll scope NLQ flows, safety requirements, and a first launch target, then propose a sprint plan or Design Capital fit. Contact Zypsy