Solutions.
We don't sell magic. We sell engineering. Here is how we help.
01. AI Readiness Assessment
Before writing code, we verify your data infrastructure and problem definition. We identify gaps between your goals and your reality.
Data Audit & Hygiene+
Analysis of your data warehouse for consistency, bias, and sparsity issues that could derail training. We check before you invest.
Infrastructure Analysis+
Evaluation of your compute stack (AWS/GCP/Azure) for scalability, security, and cost-efficiency. We prevent cloud bill shock.
Feasibility Study+
Mathematical verification that your proposed problem can actually be solved with your available data.
02. ML Model Development
Custom architectures when API wrappers fall short. We build, train, and fine-tune models that belong to you.
Custom LLM Fine-tuning+
Adapting open-weights models (Llama, Mistral) to your specific domain language and privacy constraints.
Computer Vision Pipelines+
End-to-end pipelines for meaningful extraction from video and image data, not just classification.
Predictive Analytics+
Gradient boosted trees and time-series forecasting for high-stakes business logic.
03. Technical Due Diligence
For investors and acquirers. We look under the hood to verify if the "AI" is actually AI, or just a pile of if-statements.
Code Assessment+
Static analysis and architectural review to ensure the codebase isn't a prototype masquerading as a product.
Model Reproducibility+
Can we retrain the model from scratch? If not, it's not an asset, it's a liability.
IP & Provenance+
Verifying the lineage of datasets and model weights to ensure license compliance.
04. Team Training
We level up your internal engineering team so you don't need us forever. Practical, hands-on workshops on modern ML stacks.
MLOps Hygiene+
CI/CD for models, feature stores, and automated retraining pipelines.
Architecture Workshops+
Deep dives into Transformers, Diffusion, and emerging architectures relevant to your domain.
Inference at Scale+
Strategies for low-latency serving, quantization, and edge deployment.