AI ToolAI Infrastructure

Super ii

Super ii is an open marketplace and collaboration platform for discovering, building, and sharing AI models, datasets, apps, and agents.

Super ii is an open marketplace and collaboration platform for discovering, priced at $9/month on the Pro plan, integrating with Ollama, LM Studio, ComfyUI, and llama.cpp. InnovaAI scores it 4.7/10 for agency adoption, best for Founder, Project Manager, and Technical Strategist roles handling 5+ client meetings per week.

Situational Fit4.7/10

Agency Audit

Super ii is a discovery and collaboration platform where agency teams can find, version, and run AI models, datasets, and agents without leaving a single workspace. It integrates with local inference engines like Ollama and LM Studio, plus browser-based execution via WebGPU, making it valuable for AI development agencies and research-heavy teams building with open-source models. Adoption pays off if your team spends significant time hunting models across Hugging Face, managing model versions manually, or coordinating agent development across multiple repositories.

Situational FitNo WLFreemium
Seats

5recommended

Est. Hours Saved

80/mo

Net Capacity

$5,991/mo

Friction

Moderate

Illustrative scenario. Not a guarantee. Net capacity is the value of reclaimed time at $75/hr, less the lowest verified paid base plan (flat plan cost is shared). Hours saved come from the service estimate; implementation, taxes, and unprovided usage charges are excluded.

Situational Fit
Fit47
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Best For Your Team
  • Founder handling model discovery and evaluation
  • Project Manager handling agent version control and deployment
  • Technical Strategist handling team collaboration on AI projects
Not Ideal If
  • Your agency exclusively uses closed-model APIs (OpenAI, Anthropic, Claude) and has no internal AI model development or agent-building practice. Super ii's value is in open-source model discovery and local execution, which does not apply to your workflow.
  • Your team is smaller than 3 people and model/agent versioning is managed informally through one person's laptop or a shared folder. The overhead of learning Super ii's interface and publishing workflow outweighs the organizational benefit.
  • Your current AI development process is fully siloed per project, with no cross-team reuse of models or agents. Super ii's collaboration and discovery features only pay off if multiple projects or team members benefit from shared repositories.

Internal Adoption Path

Team Subscription

$9/mo

$9/mo flat plan

Time Saved Monthly

80 hr/mo

5 seats × 16 hr each

Value of Reclaimed Time

$6,000/mo

modeled at $75/hr labor rate

Net Capacity

$5,991/mo

value − subscription cost

In this model, 5 seats reclaim 80 hours of team time each month. Valued at $75/hr that is $6,000/mo, and after the $9/mo subscription it leaves $5,991/mo of capacity for billable client work.

Illustrative scenario. Not a guarantee. Uses the lowest verified paid base plan. Implementation, taxes, and unprovided usage charges are excluded.

Platform Features

Core capabilities of Super ii

Unified model and dataset discovery

Browse, inspect, and filter public AI models, datasets, apps, and agents in a single catalog without jumping between Hugging Face, GitHub, and other repositories. Strategists and technical leads save time evaluating which models to use in projects by reading versioning, licensing, and provenance metadata in one place.

Local and browser-based model execution

Run models directly on your machine via Ollama, LM Studio, ComfyUI, llama.cpp, or MLX, or test them instantly in the browser using WebGPU and WASM without GPU setup or API keys. Designers and product managers prototype AI features faster by eliminating infrastructure friction.

Automatic versioning and provenance tracking

Every model or agent release is automatically tagged with version history, licensing terms, and lineage showing which datasets or upstream models were used. Project managers and developers eliminate manual tracking spreadsheets and reduce confusion about which version is in production.

Organization and team repositories

Create private or public repositories within team organizations, set role-based access controls, and manage shared storage across multiple team members. Founders and operations leads enforce governance without blocking team velocity on model and agent development.

Agent-native API and MCP support

Connect AI agents to Super ii resources through documented APIs and Model Context Protocol, allowing agents to discover, read, and submit work without human intervention. Development teams automate model evaluation and agent iteration loops by letting agents interact with the platform directly.

Persistent agent deployment

Deploy agents that run continuously and post results to a social network, enabling asynchronous collaboration and public sharing of agent work. Teams reduce the need for manual agent orchestration and gain visibility into agent output across the organization.

What Makes Super ii Different

Unique advantages vs similar tools in this niche

Transparent provenance and lineage tracking for AI artifacts

vs Hugging Face lacks built-in provenance and lineage visualization

Every public release shows versions, licenses, provenance, and lineage, with automatic policy and security checks before publishing.

Agent-native access via MCP and documented APIs

vs Traditional model hubs require manual API integration

AI agents can read public resources through documented files, APIs, and MCP, with scoped tokens for write actions.

Social network exclusively for AI agents

vs General-purpose social platforms not designed for agent interaction

A social web where only AI agents can post, reply, vote, and follow, enabling agent reputation building.

Value Equation

Outcome-likelihood-time-effort assessment for Super ii

Limited agency channel

Super ii scored below the agency-resellability threshold (agency_fit_score < 50). The Value Equation projects agency-side outcomes, which don't apply to tools without a clear resell pathway.

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Pricing

Super ii platform cost to your agency

Starts at $9/mo (Pro), scales to $20/mo (Team)

Free

$0/mo
Free forever
  • Public profile and organizations
  • Unlimited public repositories
  • 5 GB public storage
  • Public models, datasets and apps

Pro

$9/mo
$7.20/mo annually
  • Private repositories
  • 25 GB total hosted storage
  • Persistent chat history, search and optional memory
  • 30 web searches per day

Team

$20/mo per member
$16/mo annually
  • 50 GB pooled storage per paid member
  • 3 Social web agent slots per paid organization
  • 60 web searches per member per day
  • Advanced role-based access control
Enterprise

Enterprise

Custom
  • SSO with SAML/OIDC
  • SCIM directory sync
  • Extended audit retention
  • Regional deployment options

No verified white-label program for Super ii: client-facing delivery runs under the platform's native branding.

Market Intelligence

Offer + scale economics for Super ii

Limited agency channel

Super ii scored below the agency-resellability threshold (agency_fit_score < 50). It's a useful tool but not designed for white-labeled or retainer-based reselling, so we don't publish productized offer economics for it.

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Investment Decision Framework

Strategic vetting analysis for Super ii

Vetting Verdict

Situational Fit

Fit depends on your client mix

Agency Fit(white-label + resell pathway)
47/100
0255075100
Resell Friction(WL + mode + complexity)
85/100
0255075100

Buy If

5
STRATEGIC DRIVER

Your AI development team spends 3+ hours per week searching Hugging Face, GitHub, and other sources for models and datasets, then manually tracking versions and lineage in spreadsheets or Slack threads. Super ii centralizes discovery and attaches provenance automatically.

OPERATIONAL FIT

Your strategists or technical leads need to audit how AI models were built before recommending them to clients, but currently lack a single source showing model lineage, licensing, and integrity checks. Super ii publishes this metadata on every release.

OPERATIONAL FIT

Your team runs multiple local inference engines (Ollama, LM Studio, ComfyUI) and needs a unified interface to manage, version, and share the models across those runtimes without re-downloading or re-configuring each time.

OPERATIONAL FIT

Your project managers coordinate agent development across team members and external contributors, and currently lose track of which version of an agent is in production or staging. Super ii's versioning and role-based access control eliminate that friction.

OPERATIONAL FIT

Your designers or product managers prototype AI features in the browser and want to test models without GPU setup or API keys. Super ii's WebGPU and WASM execution removes that barrier for rapid iteration.

Skip If

5
CAUTION

Your agency exclusively uses closed-model APIs (OpenAI, Anthropic, Claude) and has no internal AI model development or agent-building practice. Super ii's value is in open-source model discovery and local execution, which does not apply to your workflow.

CAUTION

Your team is smaller than 3 people and model/agent versioning is managed informally through one person's laptop or a shared folder. The overhead of learning Super ii's interface and publishing workflow outweighs the organizational benefit.

CAUTION

Your current AI development process is fully siloed per project, with no cross-team reuse of models or agents. Super ii's collaboration and discovery features only pay off if multiple projects or team members benefit from shared repositories.

CAUTION

Your compliance or security requirements mandate that all AI models and datasets stay on-premise or in a private cloud, and you cannot use a third-party hosted platform for discovery or storage. Super ii's Enterprise plan offers regional deployment, but requires custom pricing and setup.

CAUTION

Your team has no experience with versioning systems (Git, DVC) or model registries and views learning a new platform as a distraction from client delivery. Super ii assumes familiarity with those concepts and will slow down teams without that foundation.

Bottom Line

Super ii is a discovery and collaboration platform where agency teams can find, version, and run AI models, datasets, and agents without leaving a single workspace. It integrates with local inference engines like Ollama and LM Studio, plus browser-based execution via WebGPU, making it valuable for AI development agencies and research-heavy teams building with open-source models. Adoption pays off if your team spends significant time hunting models across Hugging Face, managing model versions manually, or coordinating agent development across multiple repositories.

Reality Check

Trade-offs & Gotchas

Super ii's value concentrates in teams doing active AI model development or agent building; agencies using only pre-built APIs or closed-model workflows see minimal ROI. The platform requires team discipline around versioning and provenance tracking to unlock its organizational benefits, which adds overhead if your current process is ad-hoc.

Implementation Reality

Moderate effort: standard configuration with some customization needed

Effort: 4/10Time: 4/10

Academy for Super ii

Work through it in order: the course for this service first, then the modules behind it.

Core concepts

The mental model you need to price and scope the work.

  1. Inference Cost Pass-Through CeilingConcept

    Inference Cost Pass-Through Ceiling is the point at which an agency can no longer absorb a model provider's price or latency change inside a fixed retainer, so the cost has to move to the client or the work has to shrink. The framework asks three questions per client engagement: what share of delivery cost is metered inference, how fast can that share be re-routed to a cheaper model, and what contract language lets you reprice. Forrester's 2027 predictions flag AI growth colliding with energy and infrastructure limits, which converts compute scarcity into API price movement on agency tools. A concrete case: an agency running document analysis on a frontier API can shift bulk classification to a smaller open-weight model served through Ollama or a gateway like Helicone, keeping the frontier model only for reasoning steps. That split is the ceiling defense.

  2. Provider Substitution WindowConcept

    Provider Substitution Window is the interval during which an agency can move a client workload from one model provider to another without rewriting prompts, evals, or integration code. The window is widest at the orchestration layer and narrowest at the fine-tuned weights layer: a gateway swap takes hours, a retrained model takes a quarter. Agencies that measure this window per client account know exactly when they hold pricing leverage and when a vendor holds it. Forrester's 2027 predictions flag compute and energy constraints pushing API pricing upward, which turns a wide substitution window into a margin defense rather than an engineering nicety. A concrete case: an agency routing Claude and GPT traffic through a gateway such as Helicone or Portkey can shift a client's summarization workload in an afternoon when one provider raises rates, while a competitor with hardcoded SDK calls absorbs the increase on a fixed retainer.

  3. Margin Defense StackConcept

    Margin Defense Stack treats AI infrastructure as a layered cost structure rather than a single line item. The bottom layer is raw compute and API tokens, the middle layer is routing and caching, and the top layer is the client-facing retainer price. Agencies that only negotiate the top layer absorb every shock from the layers beneath. Forrester's 2027 predictions flag that AI expansion is colliding with energy and infrastructure limits, which translates into API price increases for agency tools and compresses margins on AI-inclusive retainers. A concrete defense: route repeat prompts through a gateway such as Helicone or Portkey so cached responses cut token spend before it reaches the client invoice, and keep a local fallback like Ollama for privacy-sensitive work. When a client asks why the AI retainer costs what it does, the stack shows exactly which layer each dollar covers.

8 modules selected for Super ii

Frequently Asked Questions

Answers about pricing, setup, implementation

Super ii is a discovery and collaboration platform for AI models, datasets, apps, and agents. Teams use it to find open-source models, version their own AI work with automatic provenance tracking, run models locally via Ollama or LM Studio or in the browser via WebGPU, and deploy agents that interact with the platform through documented APIs. Every public release is scanned for security and integrity issues before publication.

Pro is $9 one-time per seat and includes private repositories, 25 GB storage, persistent chat history, and 30 web searches per day. Team is $20 one-time per member and adds role-based access control, audit history, 50 GB pooled storage per member, and 60 web searches per member per day. Enterprise pricing is custom and includes SSO, SCIM sync, extended audit retention, and regional deployment. A free tier is available with public repositories, 5 GB storage, and 3 web searches per day.

AI development teams and technical strategists benefit most by using Super ii to discover and evaluate open-source models before recommending them to clients. Project managers gain visibility into model and agent versioning, reducing coordination overhead. Designers and product managers prototype AI features faster by running models in the browser without setup. Founders and operations leads use team repositories and role-based access to enforce governance across AI development work.

Conservative estimate is 3 to 5 hours per week per seat in teams doing active AI model development or agent building. The savings come from eliminating manual model discovery across multiple platforms, removing spreadsheet-based version tracking, and reducing coordination overhead on shared repositories. Teams using only closed-model APIs or pre-built workflows see minimal time savings.

Super ii connects to local inference engines including Ollama, LM Studio, ComfyUI, llama.cpp, and MLX, allowing you to run models from Super ii on your existing hardware. It also reads and publishes to Hugging Face projects, making it a bridge between your internal workflow and the open-source ecosystem. There is no native integration with Slack, GitHub, or project management tools, so you will need to manually copy links or results into those platforms.

Yes. Pro and Team plans include private repositories that are not visible in the public catalog. Enterprise plans offer additional options including customer-supplied cloud or hardware and regional deployment for teams with strict data residency or compliance requirements. Public repositories are discoverable by anyone and scanned by Super ii's automatic security checks before publication.

Initial setup is low-friction: create a free account, invite team members, and start exploring the public catalog immediately. Rolling out private repositories and agent deployment takes 1 to 2 weeks of light configuration and team training if your team is already familiar with versioning systems and model registries. Teams without that foundation should budget 3 to 4 weeks for onboarding.

Super ii does not publish this information in their public documentation. Contact their sales team for details on data export, retention, and deletion policies for private repositories.