Comparison
ai-serving vs catai
Verdict
Pick ai-serving if ai-Serving is an inference server supporting PMML and ONNX formats via HTTP or gRPC endpoints, easily deployable with Docker; pick catai if catai, an AI assistant framework built for local deployment with Node.js, offers developers using TypeScript the ability to create and deploy AI agents through a simple API.
Markdown twin · ai-serving alternatives · catai alternatives
GraphCanon updated Sep 20, 2026
14views this month
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Trust & integrity
| Signal | ai-serving | catai |
|---|---|---|
| Maintenance | Slowing (208d since push) As of Sep 20, 2026 · github_public_v1 | Slowing (307d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- ai-serving
- Serving AI/ML models in open standard formats PMML and ONNX with HTTP and gRPC endpoints
- catai
- Run AI assistant locally with Node.js
Stars
- ai-serving
- 166
- catai
- 500
Forks
- ai-serving
- 31
- catai
- 39
Open issues
- ai-serving
- 3
- catai
- 2
Language
- ai-serving
- Scala
- catai
- TypeScript
Adopt for
- ai-serving
- Ai-Serving is an inference server supporting PMML and ONNX formats via HTTP or gRPC endpoints, easily deployable with Docker.
- catai
- catai, an AI assistant framework built for local deployment with Node.js, offers developers using TypeScript the ability to create and deploy AI agents through a simple API.
Persona
- ai-serving
- -
- catai
- -
Runtime
- ai-serving
- -
- catai
- -
License
- ai-serving
- Apache-2.0
- catai
- MIT
Last pushed
- ai-serving
- Feb 24, 2026
- catai
- Nov 16, 2025
Categories
- ai-serving
- Inference & Serving
- catai
- AI Agents, Inference & Serving
Trust and health
Days since push
- ai-serving
- 208d
- catai
- 307d
Open issues (now)
- ai-serving
- 3
- catai
- 2
Stars delta
- ai-serving
- 0 (30d)
- catai
- +2 (30d)
Full report
- ai-serving
- Trust report
- catai
- Trust report
Choose ai-serving if…
- ai-serving is primarily Scala; catai is TypeScript.
- License: ai-serving is Apache-2.0, catai is MIT.
- Tags unique to ai-serving: ai-serving, grpc, inference-server, onnx.
- When you need to serve models in both PMML and ONNX formats without manual configuration changes between formats.
When NOT to use ai-serving
- Avoid if your team lacks familiarity or willingness to use Scala for deployment through sbt build system for customization needs.
- Not suitable when only one model format, either PMML or ONNX but not both, is needed and a simpler solution would suffice.
- If your project strictly requires a non-Dockerized setup that does not align with using pre-built Docker images.
Choose catai if…
- catai is primarily TypeScript; ai-serving is Scala.
- License: catai is MIT, ai-serving is Apache-2.0.
- Tags unique to catai: ai-assistant, chatbot, ggmlv3, llama-cpp.
- Also covers AI Agents.
- - When aiming to deploy a local AI assistant without reliance on cloud-based services; catai is ideal due to its focus on node-llama-cpp integration, allowing for robust offline capabilities.
When NOT to use catai
- - For environments that strictly prohibit or limit Node.js operations on the server side, as catai is engineered to run locally via Node.js only.
- - If seeking a cloud-based AI deployment solution that does not require local setup, since catai focuses solely on providing local AI capabilities through an easy-to-use API.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (autodeployai/ai-serving) · observed Sep 20, 2026
- GitHub forks (autodeployai/ai-serving) · observed Sep 20, 2026
- Last push (autodeployai/ai-serving) · observed Feb 24, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (withcatai/catai) · observed Sep 20, 2026
- GitHub forks (withcatai/catai) · observed Sep 20, 2026
- Last push (withcatai/catai) · observed Nov 16, 2025
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: ai-serving 166 · catai 500 (synced Sep 20, 2026).
Common questions
- What is the difference between ai-serving and catai?
- ai-serving: Serving AI/ML models in open standard formats PMML and ONNX with HTTP and gRPC endpoints. catai: Run AI assistant locally with Node.js. See the comparison table for live GitHub stats and shared categories.
- When should I choose ai-serving over catai?
- Choose ai-serving over catai when ai-serving is primarily Scala; catai is TypeScript; License: ai-serving is Apache-2.0, catai is MIT; Tags unique to ai-serving: ai-serving, grpc, inference-server, onnx; When you need to serve models in both PMML and ONNX formats without manual configuration changes between formats.
- When should I choose catai over ai-serving?
- Choose catai over ai-serving when catai is primarily TypeScript; ai-serving is Scala; License: catai is MIT, ai-serving is Apache-2.0; Tags unique to catai: ai-assistant, chatbot, ggmlv3, llama-cpp; Also covers AI Agents; - When aiming to deploy a local AI assistant without reliance on cloud-based services; catai is ideal due to its focus on node-llama-cpp integration, allowing for robust offline capabilities.
- When should I avoid ai-serving?
- Avoid if your team lacks familiarity or willingness to use Scala for deployment through sbt build system for customization needs. Not suitable when only one model format, either PMML or ONNX but not both, is needed and a simpler solution would suffice. If your project strictly requires a non-Dockerized setup that does not align with using pre-built Docker images.
- When should I avoid catai?
- - For environments that strictly prohibit or limit Node.js operations on the server side, as catai is engineered to run locally via Node.js only. - If seeking a cloud-based AI deployment solution that does not require local setup, since catai focuses solely on providing local AI capabilities through an easy-to-use API.
- Is ai-serving or catai more popular on GitHub?
- catai has more GitHub stars (500 vs 166). Stars measure visibility, not whether either tool fits your constraints.
- Are ai-serving and catai open source?
- Yes - both are open-source projects on GitHub (ai-serving: Apache-2.0, catai: MIT).
- Where can I find alternatives to ai-serving or catai?
- GraphCanon lists graph-backed alternatives at ai-serving alternatives and catai alternatives (ai-serving markdown twin, catai markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, ai-serving or catai?
- ai-serving: Slowing. catai: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for ai-serving and catai?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ai-serving trust report; catai trust report.