Production AI, accelerated. Tuned for enterprise excellence

Transform ideas into production-grade AIat supersonic speed

From rapid prototypes to massive ML pipelines. We design, fine-tune and deploy state-of-the-art models on robust data foundations. Built with Hugging Face, PyTorch, JAX, and rock-solid MLOps.

LLMs: Llama 3.1, Mistral, FalconVision: CLIP, SAM, DiffusersSpeech: Whisper, MMSPEFT, LoRA, vLLM, Triton
Advanced AI systems dashboard showing real-time model performance metrics and deployment analytics

Latency optimized with vLLM + TensorRT-LLM. Streaming tokens in < 50ms.

AI & Machine Learning Services that ship

Architecture, modeling, and delivery performed by hands-on AI researchers and production engineers.

Hyperparameter tuning
Optimized model performance through automated search and Bayesian optimization.
  • • Grid search and random search
  • • Integration with Optuna and Ray Tune
  • • GPU-accelerated experiments
Transfer learning
Efficient adaptation of pre-trained models to domain-specific tasks.
  • • Fine-tuning on custom datasets
  • • Feature extraction pipelines
  • • Cross-domain knowledge transfer
Ensemble methods
Enhanced accuracy through model combination and uncertainty quantification.
  • • Bagging, boosting, stacking
  • • Diversity maximization techniques
  • • Calibrated confidence scores
Rapid AI Prototyping
LLM apps, RAG, agents, evaluators. Turn a napkin sketch into something you can demo.

Models: Llama, Mistral, Qwen. Retrieval with ColBERT/TS. Guardrails + evals.

Model Deployment
vLLM, TensorRT-LLM, TGI, KServe. Autoscaling, canary, observability.

GPU packing, quantization (AWQ/GPTQ), KV caching, streaming, cost controls.

Deep Learning Systems
Fine-tuning with PEFT/LoRA, RLHF/RLAIF, evaluation suites, safety.

Vision (SAM, CLIP, DETR), Speech (Whisper, MMS), Multimodal (LLaVA).

Data Strategy
Data pipelines, eval/feedback loops, governance. Make data your advantage.

Feature stores, labeling, synthetic data, drift detection, privacy.

Machine Learning for Predictive Maintenance

Leverage advanced ML techniques to anticipate failures, optimize operations, and drive efficiency in manufacturing and beyond.

Predictive analytics for equipment failure
Proactive maintenance scheduling based on failure probability models and historical patterns.
Quality prediction and defect detection
In-line quality assurance using computer vision and sensor data fusion to identify defects early.
Production optimization and scheduling
Real-time resource allocation and workflow optimization using reinforcement learning and simulation.
Supply chain forecasting and logistics
Demand sensing and inventory management with multi-echelon forecasting and scenario analysis.

AI Development Engagement Models

Simple, outcome-driven pricing designed for velocity and measurable impact.

Prototype
Starter Sprint
One week to a working demo
$5,000 - $9,000 / month
  • Scoping + success metrics
  • Prototype (LLM, RAG or Vision)
  • Live demo + next steps
Most Popular
Build & Deploy
From POC to production
$20,000 - $35,000 / month
  • Team: 2 engineers + 1 researcher
  • Dedicated GPU infra + CI/CD
  • Observability, evals, guardrails
Enterprise
Lab Partnership
Scale programs & research collabs
Custom
  • Security, privacy, compliance ready
  • Multi-cloud / on-prem (K8s)
  • Advanced research sprints

AI Success Stories: Proof, not promises

We partner with product teams and research labs to ship AI outcomes that matter.

Agentic Customer Support
LLM agents trained on 300k docs
AI-powered customer support dashboard showing agent performance and response metrics
  • • -42% avg handle time, +18 NPS
  • • Safety layer with function calling and evals
Vision Quality Control
SAM + CLIP for manufacturing QA
Computer vision AI system detecting manufacturing defects in real-time quality control
  • • 97.4% defect recall at 12ms throughput
  • • On-edge deployment with TensorRT
Speech-to-Insights
Whisper + RAG for research orgs
Speech recognition AI system processing audio data for research insights
  • • 8x faster synthesis, bias-aware summaries
  • • Privacy-preserving, on VPC
"They ship research-grade work, fast."
Director of AI, Fintech
We moved from whiteboard to deployed LLM microservices in under a month. Observability and evals saved us weeks.
"The MLOps is best-in-class."
Head of Platform, SaaS
Cost per token dropped 38% after quantization and KV caching. Canary deploys gave us confidence to scale.
"A partner to our research lab."
Lead Scientist, Healthtech
We co-designed a multimodal pipeline with robust evaluation. It's now the backbone of our clinical triage.

Why Codefex AI Solutions vs DIY

With Codefex

  • Production-ready templates: vLLM, TGI, KServe
  • Evals, guardrails, drift + feedback loops baked in
  • Security and governance from day zero

Roll-your-own

  • ✕ Weeks of infra before first token
  • ✕ Hidden costs: GPUs, egress, failures
  • ✕ Hard-to-measure quality without evals