AI Models Trained on Your Data for
Your Problems
Off-the-shelf models get you 80% of the way. The last 20% — the part that actually matters for your business — requires custom training. We fine-tune and build models that understand your domain, your terminology, and your edge cases better than any generic API.
Domain Accuracy
Inference Speed
Cost Efficiency
Edge Case Handling
When Custom Models Make the Difference
Generic models fail when your data is specialized, your accuracy requirements are strict, or your terminology is domain-specific.
Credit Risk Scoring
A fine-tuned model trained on your historical lending data that predicts default probability with 22% better accuracy than generic scoring models.
FinTech & LendingMedical Document Classification
Custom NLP model that classifies clinical notes, pathology reports, and radiology findings into actionable categories — trained on 50,000+ annotated documents.
HealthcareContract Clause Extraction
A model trained to identify and extract 47 specific clause types from legal contracts — outperforming GPT-4 by 34% on your document formats.
LegalFraud Pattern Detection
Custom anomaly detection model trained on your transaction patterns that catches fraud 18% faster with 40% fewer false positives than rule-based systems.
Payments & BankingManufacturing Quality Prediction
Computer vision model trained on your production line images to detect defects at 99.2% accuracy — catching subtle quality issues human inspectors miss.
ManufacturingOur Custom Model Capabilities
From fine-tuning foundation models to training from scratch — we match the approach to your data and requirements.
LLM Fine-Tuning
Fine-tune GPT, Claude, Llama, or Mistral on your domain data. Get the reasoning power of a foundation model with accuracy on your specific vocabulary and tasks.
Custom NLP Models
Build classification, extraction, sentiment, and NER models trained on your annotated data when a fine-tuned LLM is overkill or too expensive to run.
Computer Vision Models
Train object detection, image classification, and visual inspection models on your image data — from product defects to document types.
Predictive Analytics Models
Time series forecasting, classification, and regression models built on your historical data for demand planning, risk scoring, and churn prediction.
Model Distillation
Compress large model capabilities into smaller, faster, cheaper models. Get 90% of GPT-4's quality at 10% of the inference cost for your specific task.
Continuous Retraining Pipelines
Automated pipelines that retrain models on new data, evaluate performance against baselines, and deploy updates — preventing model drift.
How We Build Your Custom Model
Data Assessment
We evaluate your training data — volume, quality, labeling, and gaps. We tell you honestly whether you have enough data or need to augment.
Approach Selection
Fine-tuning, training from scratch, or distillation? We pick the approach that matches your accuracy needs, data volume, and budget constraints.
Training & Evaluation
Iterative training cycles with rigorous evaluation against holdout test sets. We benchmark against baseline models on your actual metrics.
Optimization & Deployment
Quantization, pruning, and infrastructure optimization to get your model running fast and cost-effectively in production.
Monitoring & Retraining
Production monitoring for accuracy drift, latency changes, and data distribution shifts — with automated retraining when metrics drop.
Generic Models Give Generic Results.
Get a custom model trained on your data — free feasibility assessment with sample benchmark results.
Book Free ConsultationModels that know your business better than any API ever will.
Custom models outperform generic alternatives because they've seen your data, learned your patterns, and been tested against your real-world edge cases — not internet benchmarks.
Responsible AI Model Development
Custom models in regulated industries need explainability, bias monitoring, and governance. We build all three into the process.
Why Teams Choose Us for Custom AI Models
We've trained models that run in production — not models that impress on a benchmark and fail on real data.
Describe Your Custom Model Needs
Tell us about your data, your accuracy requirements, and the problem you're solving — we'll respond with a feasibility assessment within 48 hours.
Case Study
Online Lender Reduces Default Rate 19% with Custom Credit Scoring Model
A digital lender serving thin-file borrowers was losing $2.3M annually to defaults their generic credit model couldn't predict. Traditional credit scores missed the behavioral signals in their application and repayment data.
The Problem
Generic credit scoring models performed poorly on thin-file borrowers, leading to high default rates and missed revenue on viable applicants.
Our Approach: We trained a gradient-boosted model on 3 years of application and repayment data, incorporating 140+ features including traditional credit variables, behavioral signals, and application metadata. The model was evaluated with strict fairness audits across protected classes. SHAP-based explainability was integrated so every decision includes the top contributing factors for adverse action notices. A/B tested against the existing model for 60 days before full deployment.
Frequently Asked Questions
Use a custom model when you need speed, low cost, or small model size — classification, scoring, and extraction tasks. Use a fine-tuned LLM when you need reasoning, generation, or understanding of complex language. We'll tell you honestly which approach fits your use case.
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