Consulting & Deployment
We build production-ready AI systems. From model fine-tuning to automated MLOps, our 12-person team delivers measurable results.
Deliverables:
- Custom dataset curation and cleaning
- LoRA/QLoRA parameter optimization
- Evaluation benchmarks for domain accuracy
Deliverables:
- Real-time inference pipeline architecture
- Edge-optimized model quantization
- Automated anomaly detection triggers
Deliverables:
- Automated model retraining workflows
- Drift detection and monitoring systems
- Infrastructure-as-code deployment
Deliverables:
- Technical feasibility and ROI analysis
- Data readiness and compliance audit
- Phased implementation roadmap
Need an AI audit?
Our team will assess your data readiness and provide a clear roadmap for AI implementation.
Our AI Consulting Engagement Framework
We follow a rigorous, deterministic process to embed AI capabilities into your enterprise, ensuring production reliability and measurable outcomes.
Feasibility Assessment
Initial technical audit of your existing data infrastructure and AI readiness, identifying high-impact bottlenecks and compute requirements.
System Design
Defining the model architecture, retrieval pipelines, and latency targets required to meet your specific production performance SLAs.
Deployment Strategy
Collaborative implementation phase where our engineers embed with your team to deploy, test, and optimize the AI solution in situ.
Production Handover
Final validation of system performance, comprehensive knowledge transfer, and establishment of ongoing monitoring telemetry.
NEURALX Standard
Our engagement model prioritizes technical autonomy, ensuring your team retains full control over the AI systems we build together.