AI Product Engineering
LLM & ML Expertise
MLOps & Monitoring
Production-Grade Delivery
Agile Delivery
40+ AI Products Delivered

Why Businesses Choose Algosoft for AI Product Development

AI products engineered from prototype to production

Building an AI-based product is different from bolting an AI feature onto an existing app. It means designing the data pipeline, model architecture, and user experience together from day one. Algosoft's India-based engineering teams specialize in AI-native product development — covering everything from foundation model integration to fully custom-trained models for domain-specific use cases.

We take products through the full lifecycle: proof-of-concept validation, model training and evaluation, production deployment, and ongoing monitoring to catch model drift before it affects your users.

This service pairs with our AI development company in India for businesses needing broader AI engineering support beyond a single product build.

Entry Point$12K+AI MVP
Enterprise$220K+Full-scale AI platform
Products40+AI products delivered
ApproachAI-NativeDesigned around the model
Custom Model TrainingLLM IntegrationMLOpsProduction-ReadyAgile Delivery
AI-Native Product Design

Data pipeline, model, and UX designed together from the first sprint.

Custom Model Training

Domain-specific models trained on your data when generic APIs fall short.

MLOps & Model Monitoring

Continuous monitoring to catch model drift before it hits your users.

AI Product Development Cost

Transparent pricing for AI-based product builds

TierCost (USD)TimelineBest For
Basic$12K – $30K6 – 10 weeksAI MVP using foundation model APIs
Standard$55K – $85K14 – 20 weeksFull AI product with custom fine-tuning
Advanced$120K – $170K24 – 34 weeksCustom-trained models with production MLOps
Enterprise$220K+10+ monthsFull-scale AI platform with multiple models and integrations

Key Services We Provide

Capabilities that define great AI product development

AI Product Strategy

Defining the right model approach and data strategy before writing code.

Custom Model Training

Fine-tuned and custom-trained models for domain-specific accuracy.

LLM & Foundation Model Integration

Fast, reliable integration with leading foundation model APIs.

MLOps & Deployment

Automated pipelines for training, evaluation, and production deployment.

Model Monitoring & Drift Detection

Continuous monitoring to maintain accuracy as real-world data shifts.

Scalable Cloud Architecture

Infrastructure engineered to handle inference load as usage grows.

Cost Breakdown by Engineering Workstream

Where your AI product budget goes

16%
Data & Model Strategy

Defining the data pipeline and model approach.

36%
Model Development

Training, fine-tuning, and evaluating the core model.

22%
Product Development

Building the application layer around the model.

14%
Testing & Evaluation

Accuracy testing, bias checks, and performance validation.

8%
Deployment & MLOps

Production rollout and monitoring pipeline setup.

4%
Documentation & Handover

Technical documentation and team handover.

Why Choose Algosoft for AI Product Development?

Six reasons businesses choose us

01

AI-Native From Day One

We design the model and product together, not as an afterthought.

02

Custom & Foundation Model Expertise

We choose the right approach for your use case and budget.

03

Full Lifecycle Delivery

From proof-of-concept to production deployment and monitoring.

04

MLOps Built In

Monitoring and drift detection included, not bolted on later.

05

Agile, Transparent Delivery

Regular sprint reviews and milestone demos throughout the build.

06

40+ AI Products Delivered

AI product delivery experience across diverse industries.

Technology Stack

Technologies powering our AI products

AI/ML

PyTorchTensorFlow

LLM Frameworks

LangChainOpenAI API

Backend

PythonNode.js

Cloud

AWSGCP

Engagement Timeline

A phased roadmap from prototype to production

Weeks 1–3

Data & Model Strategy

Defining the data pipeline and model approach.

Weeks 4–13

Model Development

Training, fine-tuning, and evaluating the core model.

Weeks 14–18

Product Development

Building the application layer around the model.

Weeks 19–21

Testing & Evaluation

Accuracy testing, bias checks, and performance validation.

Weeks 22–23

Deployment & MLOps

Production rollout and monitoring pipeline setup.

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FAQ

Frequently Asked Questions

Common questions about AI-based product development

Costs range from $12,000 for an AI MVP to $220,000+ for a full-scale enterprise AI platform.

Both, depending on your use case — foundation model APIs for speed, custom-trained models for proprietary needs.

Yes, we handle the full lifecycle from proof-of-concept through production deployment and monitoring.

Yes, MLOps and drift monitoring are included to maintain accuracy as real-world data shifts.

An AI MVP takes 6–10 weeks. A full enterprise AI platform takes 10+ months.

Ready to Build Your AI-Based Product?

Get a detailed cost estimate for AI product development from Algosoft’s engineering team.

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