Fiddler AI records 44,204 monthly visits with -10.2% month-over-month growth and Contact for Pricing pricing. SuperAnnotate records 386,034 monthly visits with +37.4% growth and Free Trial, Contact for Pricing pricing.
The control plane for trusted enterprise agents and models
AI data infrastructure for building production-grade models
| Dimension / Metric | | |
|---|---|---|
| Official Domain | fiddler.ai | superannotate.com |
| Pricing Model | Contact for Pricing | Free Trial, Contact for Pricing |
| Monthly Visits | 44.2K (44,204) | 386.03K (386,034) |
| MoM Traffic Delta | -5.04K (-10.2%) | +105.05K (+37.4%) |
| Primary Market & Share | 🇺🇸 United States (28.4%) | 🇺🇸 United States (31%) |
| Direct Visits / mo | 9.13K | 248.26K |
| User Rating | 4.4 | 4.6 |
| Supported Platforms | Website | Website |
The control plane for trusted enterprise agents and models
See the performance of every agent and predictive model in a single pane of glass, with every action, token and dollar traceable by user and team.
Fiddler Centor Models power policy enforcement and continuous evaluation inside your network, avoiding external LLM API calls and their hidden costs.
Detects and redacts PII, PHI and secrets on the same request path — before a prompt reaches the model and before a response reaches the developer — with sub-80ms latency.
Keeps a living inventory of every connected agent and records each enforcement decision, with who triggered it and what happened, ready for GRC and AI regulation audits.
AI data infrastructure for building production-grade models
One configurable annotation surface for image, video, text, and audio projects, so multimodal datasets can be labeled without switching tools.
Search, filter, and inspect datasets to find the examples that will most improve a model, then route them into targeted annotation or review queues.
Dashboards for annotation volume, reviewer agreement, and project progress, plus advanced analytics on upper tiers for program-level reporting.
Metered orchestration capacity for running annotation, evaluation, and data-processing workloads, scaled by plan from roughly 1K to 10K compute hours.
Free / Open-sourceUnified observability, security and incident response for cloud-scale engineering teams
Free / Open-sourceUnified observability, security and incident response for cloud-scale engineering teams
Strong enterprise data labeling and agentic automation, but offers a distinct collaborative interface and pricing structure.
Strong enterprise data labeling and agentic automation, but offers a distinct collaborative interface and pricing structure.
SpecialistExtensive human-validated training datasets and alignment services, but lacks SuperAnnotate's self-serve software platform flexibility.
SpecialistExceptional for ML experiment tracking and LLM evaluation, but does not provide traditional computer vision data labeling environments.
SpecialistExceptional for ML experiment tracking and LLM evaluation, but does not provide traditional computer vision data labeling environments.
Free / Open-sourceAgent observability, evaluation, and continuous improvement for production AI
Free / Open-sourceAgent observability, evaluation, and continuous improvement for production AI
Excellent multimodal data infrastructure for computer vision, but lacks some of SuperAnnotate's broader enterprise project management tools.
Excellent multimodal data infrastructure for computer vision, but lacks some of SuperAnnotate's broader enterprise project management tools.
Attack-led AI security testing and red teaming
Attack-led AI security testing and red teaming
SpecialistStrong enterprise data collection and annotation services, but focuses more on managed datasets than self-serve tooling.
SpecialistStrong enterprise data collection and annotation services, but focuses more on managed datasets than self-serve tooling.
Free / Open-sourcePowerful open-source data labeling with deep customization, but requires self-hosting and lacks out-of-the-box managed enterprise workflows.
Free / Open-sourcePowerful open-source data labeling with deep customization, but requires self-hosting and lacks out-of-the-box managed enterprise workflows.
Free / Open-sourceBuild, simulate, evaluate and monitor self-improving AI agents
Free / Open-sourceBuild, simulate, evaluate and monitor self-improving AI agents
Free / Open-sourceEvaluate, monitor, and govern your AI applications in production
Free / Open-sourceEvaluate, monitor, and govern your AI applications in production
Free / Open-sourceSuperior visual dataset search and curation for computer vision, but less focused on manual text and multimodal annotation.
Free / Open-sourceSuperior visual dataset search and curation for computer vision, but less focused on manual text and multimodal annotation.
