How accurate will the model be?

We give you a realistic estimate after the data audit, not before. Accuracy depends entirely on the quality of your data and the complexity of the problem. What we can promise: honest reporting, no inflated metrics.

How long does an AI/ML project take?

Data audit and preparation: 2–3 weeks. Model development and validation: 3–6 weeks. Deployment and monitoring setup: 1–2 weeks. Total: 6–12 weeks for most projects, with a checkpoint after the data audit.

What if the model doesn't perform well enough?

We build a simple baseline model early so you can make a go/no-go decision before the full investment. You're never locked into a 12-week black box where you only find out at the end if it worked.

Do you use GPT or OpenAI?

When it's genuinely the right tool. Often a simple logistic regression or gradient boosting model outperforms GPT for structured business problems — and costs a fraction at inference. We choose what works, not what sounds impressive.

Who owns the models and training code?

You do. All models, training pipelines, data preprocessing code, and documentation are delivered to you at project end. No lock-in.

Intelligent Systems & Predictive Analytics

Custom ML Model Development — Turn Data Into Decisions, Not Just Dashboards.

AI & Machine Learning by Viprasol — delivered by the same senior team that scopes it. No hand-offs, no surprises.

Baseline model firstDrift monitoring includedYou own all models & code

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The Short Version

What's included

Our custom ML model development service turns complex business data into accurate, deployable predictions. From predictive analytics and NLP pipelines to computer vision systems, we build intelligent models that solve real problems — with honest accuracy reporting and drift monitoring baked in from day one.

Machine Learning Models

Natural Language Processing

Computer Vision

Predictive Analytics

How we work

No surprises. No handoffs.

Every step below is something we've learned from projects that went wrong. Here's exactly what working together looks like.

Do You Actually Need ML Here?

Half the AI projects I've reviewed failed because the wrong tool was chosen. Sometimes a well-designed rule-based system or a simple statistical model does the job better, cheaper, and faster than a neural network. I start by asking the uncomfortable question — and I'll tell you honestly if ML is overkill for your problem.

Deliverables

Problem framing session
ML vs. rules-based verdict
Success metrics definition
Data availability audit

Data Audit — Worse Than You Think

In every project I've worked on, the data has been messier than the client expected. Missing values, label inconsistencies, distribution shifts, leakage from the future. Expect to spend 2–4 weeks here. This is not wasted time — it's where most of the model's eventual accuracy comes from.

Deliverables

Data quality report
Leakage detection
Feature engineering plan
Labelling review

Start Dumb, Then Get Smart

I build a simple baseline first — often logistic regression or a decision tree. If it hits your target accuracy, we ship it and save you months of complexity. I only reach for deep learning when simpler models genuinely can't do the job. Complexity is a cost, not a feature.

Deliverables

Baseline model
Accuracy benchmark
Model complexity decision
Advanced model (if needed)

Validate Without Cheating

Proper train/validation/test splits with no data leakage. Honest accuracy reporting with confidence intervals, not cherry-picked metrics. I'll also test for bias — if the model performs well overall but badly for specific user groups, that's a problem worth surfacing before it becomes your problem.

Deliverables

Holdout test results
Confusion matrix & error analysis
Bias evaluation report
Confidence intervals

Ship with a Dead Man's Switch

Every model I deploy has drift detection and an automatic alert when real-world accuracy drops below a defined threshold. Models degrade silently — without this, you won't know it's broken until a customer tells you. API endpoint, monitoring dashboard, and retraining trigger all included.

Deliverables

Model API endpoint
Drift monitoring setup
Accuracy alert system
Retraining documentation

What we build

Built-in from day one

Every engagement includes these as standard — not as add-ons.

Deep Learning

Neural networks for complex pattern recognition.

Predictive Analytics

Forecast trends and outcomes with high accuracy.

NLP Solutions

Text analysis, sentiment detection, and language understanding.

Custom Models

Tailored ML models for your specific use case.

Auto-Learning

Models that continuously learn from new data.

Easy Integration

RESTful APIs for seamless integration.

Common questions

Things people usually ask

If your question isn't here, just ask us directly — we respond within 24 hours.

For classification tasks: 1,000+ labelled examples minimum, more is better. For time-series prediction: at least 2 years of clean data. We'll assess your data before quoting — anyone who promises accuracy numbers without seeing your data first is guessing.

Still have a question?

Send it directly — we read every message and respond within 24 hours, no auto-replies.

Ask us

Who we are

Available for new projects

Built to do top work. Not to scale for scale's sake.

Viprasol is a specialist technology team with deep roots in trading software, AI systems, and custom product development. We've built algo bots running on live accounts, AI pipelines processing real data, and web platforms handling real traffic — all delivered under our own name, with our reputation behind every line of code.

Most agencies grow by hiring more people. We grew by building smarter delivery systems — AI-powered workflows that let a lean team move with the speed and output of a much larger one. Faster turnaround, fewer errors, a senior expert on every project from first call to final handover.

We're selective about what we take on. Not to be exclusive — because doing fewer things properly is the only way to protect the quality we're known for.

100+Projects shipped

3+Years of specialist builds

0Junior handoffs — ever

Specialists, not generalists

Trading, fintech, AI, and custom tech. We go deep on what we know rather than wide on everything.

Senior on every project

The person you speak to is the person who builds it. No hand-offs, no juniors assigned to save margin.

AI-powered delivery

Our internal AI systems let a lean team move with the speed and quality of a much larger one.

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Ready to Leverage AI for Your Business?

Let's explore how artificial intelligence can transform your operations.

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No commitment requiredResponse within 24 hoursYou talk to the person who builds it