How we build
From frontier-level capability to a model you can run.
Every Konic family is produced by the same pipeline: pick the workload, adapt an architecture, compress it to the hardware, verify against the bar.
- 01
Specialization — domain knowledge integration
Ingest and structure the client's corpora, tools, and workflow traces so the model internalizes how the business acts.
- 02
Efficiency — pruning and distillation
FFN-width pruning, router-weighted expert pruning, and distillation-to-baseline alignment cut compute and memory while a teacher keeps the quality bar. Research →
- 03
Quantization — INT4 deployment artifacts
AWQ group-wise INT4 with per-channel scaling and norm folding; artifacts load in vLLM, MLX, llama.cpp. AWQ INT4 on Qwen3-8B →
- 04
Verification — measured, not claimed
A/B against the incumbent model or the client's success criteria; decide on numbers.
Market landscape
Everyone ships a layer. We ship the model as a product.
Closest analogues combine only part of the picture. Mistral and a small set of optimization startups each cover a slice — versioned families, on-premise licensing, and custom model development exist separately. Konic ships them as one supported offering.
Landscape
Where each option stops
What the market delivers versus what it leaves open for the enterprise buyer.
| Category | What they deliver | What it leaves open |
|---|---|---|
| Frontier API | A general-capability model behind a per-token API — instant to start, priced for every use case. | Cost scales with usage, data leaves the institution, and serving decisions stay external. |
| Inference platforms | Infrastructure to serve someone else’s model on managed GPUs. | Model selection, tuning and results remain the customer’s problem. |
| GPU-vendor runtimes | An optimized serving container for self-hosting. | Model adaptation, evaluation and lifecycle remain unsolved. |
| Open-weight checkpoints | A free file to download and run. | Compression, post-training and serving all fall on the customer’s team. |
| Konic model families | A supported, versioned model family deployed on the customer’s own hardware with an annual licence that does not scale with usage. | Nothing structural — the model is the product: integration, evaluation and lifecycle stay covered. |
Own your enterprise AI.
Start with one workload and measured success criteria — we bring the pipeline most enterprises cannot staff.