Hyper-Parameter Optimization Active

Neural
Distillation

Generic models aren't enough for the enterprise. We forge custom weights using **LoRA, QLoRA, and Full-Parameter Tuning** to bake your proprietary domain expertise into the model's core architecture.

Step 01

Cleanse

Data Curation

Step 02

Forge

Weight Tuning

Step 03

Align

RLHF Loop

Step 04

Deploy

Model Quantization

LIVE_LOSS_CONVERGENCECluster: H100_NODE_4

Learning Rate

2e-5

Validation Error

0.0042

LOG:Applying Low-Rank Adaptation (LoRA) to Self-Attention layers... Memory efficient mode enabled.

Refining
The
Synapse.

We specialize in **Parameter-Efficient Fine-Tuning (PEFT)**. This allows us to deliver high-performance, specialized models that fit on consumer hardware without sacrificing the reasoning depth of foundation models.

Quantized Distillation

Compressing 70B models into 8-bit or 4-bit precision with zero accuracy loss.

Custom RLHF

Aligning models to your corporate ethics and safety guidelines through human feedback.

Vector Embeddings

Training custom embedding models for industry-specific semantic search.

Massive Scale Compute

Dedicated H100 and A100 clusters optimized for rapid iteration.

Total FLOPs

420.5 Peta

Interconnect

NVLink 4.0

SLA Uptime

99.995%

Own Your
Intelligence

Stop relying on public APIs. Train a model that is legally and technically yours.

Compute Node // Gurugram, India