GeekyAnts
Artificial Intelligence Consulting

ML Strategy and Model Discovery

We help you leverage machine learning for your business goals. We deliver pragmatic model development that supports business logic: fine-tuning and optimization where it matters, and lean deployments when cost/latency matters.

Machine learning research often hits a wall when it meets real-world constraints. A model that is accurate in a test environment can still be too slow for your users or too expensive to keep running. We see many projects fail because the engineering side was overlooked during the planning phase.


We help you leverage machine learning and make it a worthwhile investment. We look at the full picture of your data and your infrastructure to find the most efficient path forward. This results in a system that solves real problems without becoming a technical burden. Our partners value this because it turns complex problems into a functional, scalable product.

CUSTOMER STORIES

Client Results and Success

Document Intelligence Platform

99% reduction in manual effort

The solution handles thousands of pages, summarises information, and gives accurate, reliable answers within seconds - dramatically improving speed, consistency, and decision-making.

2 mins

For 1,000–10,000 pages processing

85%+

Accuracy in responses

95%+

Contextual relevance

Architecture Review Assistant

88.33% reduction in TAT for review

The assistant helps tech leads refine their designs so architecture boards receive cleaner, more complete diagrams. This helps teams catch early mistakes, improve quality, and reduce rework.

<1 hr

Tech architecture review time

~70%

Accuracy in identifying issues

95%

Contextual relevance

Automated Reporting & Insights System

99% faster turnaround time for report creation

This system relies entirely on the organization’s own data, ensuring zero bias in all outputs

<1 min

Report turnaround

~85%+

Accuracy in generated reports

~85%

Contextual relevance of insights

Property Inspection Chat Assistant

90% property-data relevance during on-site queries

The assistant delivers accurate responses, while automatically routing sensitive or price-related questions to the admin team to ensure control and compliance.

80%

answer accuracy

~90%

relevance to the property data

2x faster

On-site interactions with voice-enabled queries

Personalized Meal Recommendation System

80% recommendation accuracy

The system analyzes user preferences to provide tailored meal suggestions for every day. This helps the platform drive higher engagement and ensures users find recipes they actually want to cook.

80%

Recommendation accuracy

AI Assisted Clinical Documentation for Dentists

95% accuracy in diagnosis and prescription generation

The platform turns dental conversations into automated medical notes and prescriptions instantly. This allows dentists to approve reports with a single click and stay focused on their patients.

~95%

Accuracy in generated reports

~95%

Contextual relevance

WHAT WE DO

Our Capabilities

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RAG Optimization

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Model Fine-Tuning

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Small Language Model Strategy

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Data Engineering & Curation

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MLOps & Performance Monitoring

What You Get

We Help You Move Beyond Guesswork

Many AI projects start with early assumptions about how a model will perform. We replace those assumptions with technical data and clear benchmarks. Our approach is straightforward: Build for reliability. Align with business logic. Scale with efficiency.

What You Get

  • Full visibility into data pipelines

  • Technical proof for every model decision

  • A shared roadmap for engineering and business teams.

    • WHY TRUST US

    What You Get From a Partnership With GeekyAnts

    These are the concrete outcomes of our engagement:
    A detailed report comparing different models to find the most cost-effective fit for your specific task.
    Clear data showing exactly how much performance improved after fine-tuning or RAG customization.
    A blueprint for where your model lives—whether in the cloud or on the edge—and how we track its health in production.
    A practical guide to keeping your data safe and your models accurate as your requirements change over time.

    FEATURED CONTENT

    Our Latest Thinking in AI/ML

    Discover the latest blogs on Our Latest Thinking in AI/ML, covering trends, strategies, and real-world case studies.
    Why Your First AI Pilot Needs Success Metrics Before Development Begins
    Business

    May 28, 2026

    Why Your First AI Pilot Needs Success Metrics Before Development Begins

    95% of AI pilots deliver zero measurable profit impact. Learn the critical importance of establishing concrete success metrics and operational constraints before writing any code to ensure your project scales.

    Building Production-Ready AI Portfolio Management Platforms for Wealth Firms
    Business

    May 27, 2026

    Building Production-Ready AI Portfolio Management Platforms for Wealth Firms

    This guide walks platform leaders through production architecture, real-time data pipelines, legacy system integration, regulatory compliance, and the build-buy-modernize decision framework for deploying an enterprise-grade AI portfolio management platform.

    Building an AI Fintech Robo-Advisor Platform: Architecture, Compliance, and Key Features
    Business

    May 26, 2026

    Building an AI Fintech Robo-Advisor Platform: Architecture, Compliance, and Key Features

    A technical guide for CTOs and engineering leaders on building a compliant, production-grade AI robo-advisory platform for the US market, covering architecture, compliance, and cost.

    AI in Insurance: Building Production-Ready Products for Claims, Underwriting, and Customer Experience
    Business

    May 22, 2026

    AI in Insurance: Building Production-Ready Products for Claims, Underwriting, and Customer Experience

    This blog breaks down what it takes to build production-ready AI in insurance across claims, underwriting, and customer experience. It covers the gap between AI pilots and live deployments, the architecture and governance requirements that determine whether a system holds up at scale, and what insurers need to get right across data infrastructure, compliance, and human oversight before going live.

    Cursor vs. Lovable vs. Replit: Which Vibe Coding Tool Builds the Most Production-Ready Code?
    Business

    May 21, 2026

    Cursor vs. Lovable vs. Replit: Which Vibe Coding Tool Builds the Most Production-Ready Code?

    This guide breaks down Cursor, Lovable, and Replit across the criteria that matter most to CTOs, founders, and engineering leaders, making platform decisions with real operational consequences.

    Explainable AI in Insurance Underwriting: Balancing Accuracy and Compliance
    Business

    May 21, 2026

    Explainable AI in Insurance Underwriting: Balancing Accuracy and Compliance

    Discover how XAI helps insurers improve underwriting accuracy while meeting regulatory, auditability, and transparency requirements.

    View all blogs

    Ready to Turn ML Investment to ROI?

    Schedule a technical discovery session with our machine learning team today.

    Trusted By

    Book a Discovery Call

    Ready to Turn ML Investment to ROI?

    Schedule a technical discovery session with our machine learning team today.

    Trusted By

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