SofStack is an AI MVP development company that helps enterprises and established businesses turn AI ideas into working, production-ready products in weeks, not quarters.
Most enterprise AI initiatives stall between a promising demo and a product people actually use. We close that gap. Our teams scope the use case, validate it on your real data, and build an MVP with the security, integrations and governance your organisation needs to approve it.
Since 2018, SofStack has delivered custom software and AI systems for clients worldwide from our engineering centre in Noida, India.
Who We Work With
We work with business and technology leaders who need an AI product shipped with accountability:
CTOs and VPs of Engineering who need extra AI delivery capacity without hiring a full team
Innovation and digital transformation heads validating AI use cases before a wider rollout
Product leaders adding AI features or launching a new AI product line
Operations and business unit heads automating document-heavy or repetitive workflows
Mid-size and large companies that need a reliable offshore AI development partner
AI MVPs We Build for Enterprises
Generative AI Copilots and Assistants
LLM-powered assistants for employees and customers, grounded in your internal knowledge through retrieval-augmented generation (RAG).
AI Agents and Workflow Automation
Agents that complete multi-step tasks across your CRM, ERP, ticketing and internal tools, with human approval where it matters.
Document and Data Intelligence
Extraction, classification and summarisation for contracts, invoices, claims, reports and other business documents.
Predictive and Analytics MVPs
Forecasting, scoring and anomaly detection models wrapped in dashboards and APIs your teams can use every day.
AI SaaS Products
New AI products with multi-tenant architecture, user roles, billing and usage tracking, ready for your first customers.
Engagement Models
Start small, prove value, then scale. Each stage gives you a clear decision point before the next investment.
Engagement | Best for | Duration | Outcome |
Paid Discovery | Unclear scope or data readiness | 2 weeks | Use-case scope, architecture and costed build plan |
AI Proof of Concept | Testing feasibility on real data | 3–4 weeks | Working POC with success metrics and a go/no-go report |
AI Pilot | Testing with real users | 6–8 weeks | Integrated pilot measured against business KPIs |
AI MVP Build | Launching a usable product | 8–12 weeks | Production-ready MVP with documentation and handover |
Dedicated AI Team | Ongoing roadmap delivery | Monthly | AI engineers and a delivery lead embedded in your roadmap |
Our AI MVP Delivery Process
Discovery and scoping: We define the business problem, success metrics, users, data sources and constraints with your stakeholders.
Data and feasibility check: We test model approaches on a sample of your real data and confirm what accuracy and cost are achievable.
Architecture and plan: We agree on the technical design, integrations, security approach, milestones and acceptance criteria.
Iterative build: We build in two-week sprints, with a demo and progress report at the end of each sprint.
Testing and evaluation: We run functional, security and AI quality tests, including accuracy, hallucination and edge-case checks.
Launch and handover: We deploy to your cloud, train your team and hand over code, documentation and runbooks.
Security, IP and Compliance
Enterprise AI projects need to pass security and legal review. We build with that in mind from day one.
NDA before discovery and confidentiality across the whole engagement
Full IP ownership: all code, models and documentation transfer to you
Your cloud, your data: deployment on your AWS, Azure or Google Cloud account
Data privacy by design: GDPR-aware and HIPAA-aware handling of personal and sensitive data
Access control: role-based access, audit logs and secrets management
Vendor review support: we complete your security questionnaires and documentation requirements
AI Capabilities and Tech Stack
Layer | Technologies |
LLMs and models | OpenAI GPT, Anthropic Claude, Google Gemini, Llama, Mistral, custom ML models |
AI frameworks | LangChain, LlamaIndex, CrewAI, Hugging Face, PyTorch, scikit-learn |
Retrieval and data | Pinecone, Weaviate, pgvector, PostgreSQL, MongoDB, Snowflake |
Backend and APIs | Python, FastAPI, Node.js, Java, REST and GraphQL |
Frontend | React, Next.js, React Native |
Cloud and MLOps | AWS, Azure, Google Cloud, Docker, Kubernetes, CI/CD, model monitoring |
Enterprise AI MVP Use Cases
Internal Knowledge Assistant
A secure assistant that answers employee questions from policies, manuals and project documents, with source citations and access controls by department.
Claims and Invoice Processing
An AI pipeline that extracts fields from incoming documents, validates them against business rules and routes exceptions to a human reviewer.
Sales and Support Copilot
A copilot inside your CRM or helpdesk that drafts replies, summarises account history and suggests next actions for each customer.
Demand and Risk Forecasting
Forecasting models that predict demand, churn or risk, delivered through a dashboard and an API for existing business systems.
Why Enterprises Choose SofStack
Delivery focus: execution is our core strength, with fixed milestones and weekly reporting
Senior AI engineers: experienced engineers on your project, supported by a dedicated delivery lead
Offshore cost advantage: enterprise-quality delivery from India at a fraction of US and EU agency rates
Time-zone overlap: working hours planned around your team in the US, UK, Europe, Middle East or APAC
Built to scale: MVP architecture designed to grow into a full product without a rewrite
Experience since 2018: years of custom software and AI delivery for global clients
AI MVP Development Pricing
Pricing depends on scope, data complexity, integrations and compliance requirements. These ranges show typical starting points.
Engagement | Starting price | Timeline |
Paid Discovery | From $2,500 | 2 weeks |
AI Proof of Concept | From $5,000 | 3–4 weeks |
AI Pilot | From $10,000 | 6–8 weeks |
AI MVP Build | From $15,000 | 8–12 weeks |
Dedicated AI Team | From $6,000/month | Monthly |
We work on fixed-price milestones or monthly team contracts, with invoicing that fits your procurement process.
Frequently Asked Questions
What does an AI MVP development company do?
An AI MVP development company designs and builds the first usable version of an AI product. It covers scoping, data validation, model selection, application development, testing and deployment, so you can test the product with real users before investing in a full build.
How long does it take to build an enterprise AI MVP?
Most enterprise AI MVPs take 8 to 12 weeks. Regulated industries or complex integrations can take 10 to 14 weeks. A proof of concept can be ready in 3 to 4 weeks.
How much does AI MVP development cost?
SofStack AI MVP builds start from $15,000. The final cost depends on scope, data readiness, integrations and compliance needs. A paid discovery gives you a fixed quote before you commit.
Do we own the code and the AI models?
Yes. All source code, model configurations, prompts and documentation are transferred to you. We sign an NDA before discovery begins.
Can you work with our existing systems and cloud?
Yes. We deploy on your AWS, Azure or Google Cloud account and integrate with your CRM, ERP, databases and internal APIs.
How do you keep our data secure?
We use role-based access, encrypted storage, audit logging and data minimisation. Sensitive data stays in your environment wherever possible, and we follow GDPR-aware and HIPAA-aware practices where they apply.
Do you work with companies outside India?
Yes. Most of our clients are in the US, UK, Europe, the Middle East and APAC. We plan working hours to overlap with your team.
What happens after the MVP launches?
You can take the product in-house with our handover documentation, or continue with SofStack through a dedicated team for scaling, new features and ongoing model improvements.
Start Your Enterprise AI MVP
Tell us about your AI use case. We will reply within one business day with next steps and a recommended starting engagement.