Avatar SDK's answer

Avatar SDK is built by Itseez3D, founded in 2014 and headquartered in Santa Clara, California, by engineers with deep roots in computer vision and the OpenCV community. The company started with 3D face and body scanning and evolved into a platform that reconstructs recognizable, fully rigged 3D avatars from a single photo. Today it powers avatar creation across games, VR/AR, e-commerce/virtual try-on and virtual-identity products, offered as an embeddable creator (MetaPerson), SDKs, and a Cloud API.

TranscriptFetch's answer:

It started with discovering there is no good way to get the text of a video. YouTube’s official Data API will confirm a caption track exists and then refuse to hand it over, because captions.download requires the video owner’s OAuth token. The popular open-source libraries work until you deploy them, at which point platforms start refusing datacenter IPs. And YouTube is the easy case: TikTok and Instagram publish no caption file at all. Every workaround solved one platform, worked locally, and broke in production. TranscriptFetch is the version that handles the failure cases as first-class behaviour rather than edge cases.

Avatar SDK's answer

Computer vision and deep learning for photo-to-3D reconstruction; a 3D graphics pipeline that outputs rigged meshes with facial blendshapes and a Mixamo-compatible skeleton; standard 3D formats (GLB/glTF and FBX); and delivery through SDKs for Unity, Unreal Engine, iOS, Android and Web plus a Cloud REST API. On the web, avatars integrate with three.js and Babylon.js, and Local Compute enables on-premise/offline generation.

TranscriptFetch's answer:

Next.js with TypeScript and Tailwind on the front end and API layer, Clerk for auth with SHA-256 hashed API keys, Neon Postgres with Drizzle ORM, Redis for caching, and Stripe for billing. The extraction layer is a Python and FastAPI service. Speech-to-text uses Whisper-class models. The MCP server is published in the official Model Context Protocol registry with a DNS-verified namespace.

Avatar SDK's answer

Avatar SDK turns a single selfie into a fully rigged 3D avatar — head or full-body, realistic or cartoon — and delivers it three ways: an embeddable browser-based creator (MetaPerson), native SDKs for Unity, Unreal Engine, iOS, Android and Web, and a headless Cloud REST API for server-side generation. Every avatar has facial blendshapes and a Mixamo-compatible skeleton and exports to standard GLB/glTF and FBX, so it loads into Unity, Unreal, Blender, three.js and Babylon.js with no conversion. It runs in the cloud or fully on-premise/offline via Local Compute.

TranscriptFetch's answer:

Most short-form video has no caption track to download. TikTok’s auto-captions are opt-in per upload, Instagram never publishes a downloadable track, and many captions on both are burned into the video frames where no parser can read them. TranscriptFetch transcribes the audio when no caption track exists, on the same endpoint, with the same response shape. Your code never branches on which method produced the text. It also covers YouTube, TikTok, Instagram, X and Facebook plus any web page as clean Markdown, so a pipeline spanning several sources is one integration rather than five.

Avatar SDK's answer

Avatar SDK combines production-ready avatar quality with unusual flexibility in integration and deployment. Unlike cloud-only tools, it can run fully on-premise/offline via Local Compute, and it exports open GLB/glTF and FBX with no lock-in. It offers both an end-user creator you can embed and a headless Cloud API for automated pipelines, plus native SDKs for Unity, Unreal, iOS, Android and Web. It's built by Itseez3D, an independent company shipping avatar technology since 2014 — and after Ready Player Me shut down in 2026, it became one of the main production-ready migration paths.

TranscriptFetch's answer:

Three reasons. Coverage: one API key and one response shape across five video platforms and the open web, instead of stitching together a library per platform. Reliability: requests run through rotating infrastructure, so code that works locally keeps working from a server, which is where most open-source approaches break. Billing that matches reality: one credit per successful response, with failed, blocked and empty results never charged. That last point matters on short-form video, where a meaningful share of any batch is music with no speech in it. There is also an MCP server, so AI agents can fetch transcripts as a tool without a custom integration.

Avatar SDK's answer

Developers and enterprises adding avatars to their products — game studios, VR/AR apps, e-commerce and virtual try-on, metaverse and virtual-identity platforms, and marketing teams. It serves indie and mid-size developers through the Pro plan and the embeddable MetaPerson creator, and larger companies through the Enterprise Cloud API and on-premise Local Compute. The common thread: teams that need recognizable, rigged 3D avatars from a photo without building the pipeline themselves.

TranscriptFetch's answer:

Developers and technical teams building on video and web content. The common cases are RAG and retrieval pipelines that need video as text, AI agents that need to read a link mid-conversation, content teams repurposing short-form video at scale, and media monitoring and research tools. It is an API first, so the buyer is usually the person writing the integration rather than an end user. The free browser tools exist for one-off transcripts and for evaluating output quality before writing any code.