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ollaya

Run open decision models locally: pull and serve Laya, decider, NLI and GLiClass behind a TypeSafe-compatible API. Ollama for decision models.

Details

External ID
1384260430
Source
GITHUB
Company
—
Product
ollaya
Website domain
ollaya.dev
Launched
Sept. 23, 2026
Cohort
—
Upvotes
625
Upvotes percentile
0.9915449654112222
Tags
calibration, classification, decision-models, gliclass, jev, laya, llm-routing, local-inference, nli, ollama, onnx, onnxruntime, rust, typesafe, zero-shot-classification
Fetched at
Sept. 27, 2026, 5:02 p.m.
Updated at
Sept. 27, 2026, 5:02 p.m.

Enrichment

Theme
decision model runtimes and tools
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
local runtime and api server for decision models
Manually corrected
False

Could you build this?

Partial Wrapping open decision models (Laya, GLiClass, NLI) in a local Go/Rust/Python CLI server with a drop-in API is feasible, but high-throughput single-digit millisecond GPU inference and quantization orchestration requires non-trivial systems work.

What it would actually take: The architecture involves a local HTTP daemon (written in Go or Rust) that embeds or communicates with a lightweight Python/C++ inference runtime (ONNX Runtime, LibTorch, or TensorRT). The hard parts are efficient memory mapping, dynamic batching, zero-copy tensor parsing, and maintaining low-latency execution (<10ms) across heterogeneous GPUs.

Competitors

Other products that read as similar to this one — 325 launches clear the similarity bar, closest 8 shown.

Attention rank: #10 of 326 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 324 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a model & infra tool for Fintech yet.