Task-specific model development.
Konic turns repeated production behavior into compact language models trained around defined objectives.
Task boundary definition
Compact model training
Model adaptation
konicTailored micro LLMs
for on-prem production AI.
konic works directly with teams to design, evaluate, and deploy compact task-specific micro LLM models for production AI environments.
Production AI belongs on purpose-built models.
Model infrastructure, not workflow wrappers.
Konic builds compact language models trained, evaluated, and deployed for defined production objectives.
Task-specific intelligence with measurable boundaries.
Each model is shaped around clear behavior, benchmarked against cost, latency, quality, and control.
Smaller models for production inference.
Konic replaces repeated broad-model inference with specialized LLMs designed for efficient serving.
What Konic builds for production AI.
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Evaluation and benchmark systems.
Measure specialized models against broad-model baselines across quality, cost, latency, and control.
Task-level benchmarks
Baseline comparison
Regression tracking
Production inference infrastructure.
Deploy smaller models for efficient, controllable serving in private or on-prem production systems.
Low-latency serving
Cost-aware inference
Private deployment
Model iteration lifecycle.
Improve specialized models through data feedback, evaluation runs, and controlled releases.
Dataset refinement
Versioned models
Continuous evaluation
Models
Micro LLMs, tailored for production
Konic works with AI teams to build compact task-specific micro LLM models, evaluation harnesses, and private deployment paths for repeated production AI workloads.
Private model deployment
Deploy tailored micro LLMs inside customer-controlled infrastructure, including on-prem and private cloud environments.
Tailored specialization
Fine-tune, distill, and adapt compact models around a specific production task and success criteria.
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We start with a repeated workflow, define the model boundary, and scope deployment around your infrastructure.
Research
Model work made measurable.
Konic documents evaluation design, model behavior, deployment tradeoffs, and iteration history during tailored micro-model engagements.
01 / Model reports
Task model reports for each engagement.
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Build a tailored micro LLM for your production workflow.
Konic works directly with teams to define, evaluate, specialize, and deploy compact task models in private or on-prem environments.
Project fit
The best starting point is a narrow production task with real examples, measurable quality targets, and a clear deployment boundary.
Repeated workflow with clear inputs and outputs
Private or on-prem deployment requirements
Existing examples, labels, policies, or evaluation criteria
Production pressure around cost, latency, control, or review rate
Define the task boundary
Map the workflow, expected outputs, unacceptable failures, and deployment constraints.
Build the evaluation harness
Compare tailored micro models against broad-model baselines using task-level metrics.
Deploy inside your environment
Ship model weights, serving, monitoring, and iteration loops around your infrastructure.