Engineering AI-Powered
Products and Platforms
App Engineering
Design and deploy cloud-native web and mobile applications. We leverage microservices and serverless architectures to ensure your products scale seamlessly.
GenAI & LLMs
We integrate Generative AI and custom LLMs specifically tuned to your business logic, providing intelligent, context-aware automation and insights.
Data Engineering
Architecting robust data pipelines and high-performance warehouses that turn raw information into a strategic asset for your enterprise.
Brand Narrative
Arithmetic Infotech is a global AI-native engineering company
We build enterprise-grade products, platforms, and AI systems for companies that need more than experimentation. Our teams blend AI research literacy with production engineering, delivering systems that are reliable, secure, and ready for global scale.
AI-Native by Design
Every solution starts with the AI system model: data flows, retrieval patterns, safety, and model strategy. We build with production constraints in mind from day one.
- 1Model and data strategy first
- 1Safety, reliability, and cost considered early
- 1Proofs tied to production readiness
Architecture-Led Delivery
We lead with architecture: contracts, observability, deployment topologies, and runbooks. Design decisions are documented and measurable.
- 2API-first contracts and SLIs/SLOs
- 2Observability, governance, and compliance paths
- 2Deployment blueprints and playbooks
Outcome-Driven Engagements
We measure success by shipped, stable systems and business outcomes, not demos. Engagements map to ROI, resiliency, and adoption metrics.
- 3Business outcomes mapped to engineering KPIs
- 3Stability, latency, cost as first-class metrics
- 3Change management and enablement baked in
Core Engineering Capabilities
We build intelligent systems by combining deep technical expertise in AI, cloud infrastructure, data engineering, and modern application development. These are engineering capabilities, not marketing services.
GenAI & LLM/SLM Engineering
Unlock transformative business value with bespoke AI solutions and next-generation language models. We architect intelligent systems that drive innovation, automate complex workflows, and deliver measurable impact for forward-thinking organizations.
- Custom LLM development and fine-tuning
- RAG (Retrieval-Augmented Generation) systems
- AI agents and tool orchestration
- Prompt engineering and optimization
- Secure, enterprise-ready GenAI architectures
- Foundation model integration (GPT, Claude, Llama)
AI-Powered Mobile App Development
Deliver unforgettable mobile experiences powered by cutting-edge AI. From conversational interfaces to advanced vision and voice features, our apps engage users and elevate your brand with seamless intelligence and reliability.
- React Native and Expo development
- AI chat interfaces with streaming responses
- Computer vision and image processing
- Voice recognition and speech synthesis
- Document intelligence and OCR
- Offline-first architectures with AI sync
Cloud & Platform Engineering
Empower your enterprise with resilient, scalable, and secure cloud platforms engineered for AI and mission-critical workloads. Our cloud solutions optimize costs, accelerate innovation, and ensure your business is always ready for what’s next.
- Azure-native system design and deployment
- Microservices and API gateway architectures
- Container orchestration (Kubernetes, AKS)
- Secure authentication and identity management
- Cost-optimized AI infrastructure
- DevOps and CI/CD automation
Data Engineering
Supercharge your data strategy with a team fluent in the entire data engineering spectrum—from Databricks and Palantir Foundry to legacy platforms and modern cloud data warehouses. We architect future-proof data ecosystems that fuel AI, analytics, and business growth, ensuring your enterprise is always ahead of the curve.
- Advanced Databricks engineering and Lakehouse architectures
- Palantir Foundry data pipelines and operational analytics
- Microsoft Fabric for unified analytics and data integration
- Legacy platform expertise: Hadoop, Cloudera, HortonWorks, MapR
- Snowflake and cloud-native data warehouse solutions
- ETL/ELT orchestration and real-time data processing
- Feature stores, vector databases, and ML-ready data
- Data quality, observability, and governance
Application Development
Accelerate your digital transformation with full-stack product engineering that blends creativity, speed, and technical excellence. We build scalable, high-performance applications that delight users and drive business success.
- Next.js, React, and TypeScript applications
- FastAPI and Python backend systems
- API-first and headless architectures
- SaaS and internal platform development
- Real-time features and WebSocket integration
- High-performance, scalable systems
Legacy Support & Modernization
Revitalize your legacy systems with seamless modernization and AI augmentation. Our experts ensure minimal disruption while unlocking new capabilities, efficiency, and value from your existing technology investments.
- Legacy application support and maintenance
- System refactoring and re-architecture
- Database and data migration
- API modernization and integration
- AI augmentation of legacy workflows
- Phased modernization strategies
Ready to elevate your business with world-class engineering? Let’s create something extraordinary together.
Start Your Transformation JourneyCapability Playbooks
Deep engineering playbooks for every capability
Each capability has an execution playbook with architecture references, checklists, SLAs, and runbooks. We tailor them to your domain, data, and compliance needs.
GenAI & LLM Engineering
PlaybookCustom models, retrieval, safety, and evaluation.
- Model selection, fine-tuning, and distillation
- RAG blueprints: chunking, indexing, retrieval policies
- Guardrails, evaluations, and red-teaming
- Latency and cost optimization for inference
AI-Powered Digital Experiences
PlaybookMobile, web, and multimodal interfaces with AI-native patterns.
- Streaming chat and agentic flows
- Voice, vision, and document intelligence
- Personalization and experimentation frameworks
- Edge/offline strategies with sync to cloud
Data & Platforms
PlaybookData foundations that make AI reliable and observable.
- Ingestion, quality, lineage, and governance
- Vector stores, feature stores, and lakehouse patterns
- Telemetry, observability, and FinOps for data/AI
- ML lifecycle: labeling, training, deployment
Enterprise Architecture
PlaybookCloud-native, zero-trust, and compliance-aware systems.
- API gateways, service meshes, and contract-first design
- Identity, secrets, and policy enforcement
- Resilience engineering and chaos testing
- Disaster recovery, RPO/RTO planning
How We Engineer
Our engineering process emphasizes technical rigor, iterative development, and production-grade quality. We build systems that are secure, scalable, and maintainable over the long term.
Problem Understanding & Feasibility
Deep discovery to understand business context, technical constraints, and engineering requirements. We assess AI/ML feasibility, data availability, and system integration needs.
Architecture & AI System Design
Designing scalable, secure, and cost-effective system architectures. We define data flows, model selection, API contracts, and infrastructure requirements.
Iterative Product Development
Building production-grade systems using modern engineering practices. We prioritize working software, continuous integration, and regular stakeholder feedback.
Production Deployment & Hardening
Deploying systems with monitoring, observability, and security hardening. We ensure performance, reliability, and operational readiness.
Continuous Optimization & Support
Ongoing system monitoring, AI model refinement, and feature enhancements. We provide long-term support and continuous improvement.
Engineering Principles We Follow
AI & System Architecture
Our systems are built on modern, cloud-native architectures that prioritize security, scalability, and operational excellence. We design for production from day one.
Architecture-first, production-forward
Every engagement starts with architecture: contracts, observability, risk, and runbooks. We keep decision records, measurable SLIs/SLOs, and deployment paths aligned to your compliance posture.
Design Artifacts
- Architecture decision records (ADRs)
- API contracts and integration maps
- Data, security, and failure mode diagrams
Operational Readiness
- SLIs/SLOs for latency, availability, and cost
- Runbooks, on-call, and incident response paths
- Evals, guardrails, and rollout plans for AI
Governed Delivery
- Change management with feature flags
- Auditability, logging, and tracing standards
- Compliance-aligned deployment strategies
Typical System Architecture
Client Layer
API Gateway & Backend
AI & ML Layer
Data Layer
Infrastructure
Architecture Pillars
Security
End-to-end encryption, secure authentication, role-based access control, and compliance with data protection regulations.
Scalability
Horizontally scalable architectures, auto-scaling infrastructure, load balancing, and efficient resource utilization.
Observability
Comprehensive logging, distributed tracing, real-time monitoring, alerting, and performance analytics.
Cost Control
Optimized cloud resource usage, efficient AI model serving, caching strategies, and cost monitoring dashboards.
Core Technology Stack
Want to discuss your system architecture requirements?
Talk to Our ArchitectsEnterprise Readiness
Built for security, governance, and scale
Enterprise programs demand rigor. We design AI systems with controls for security, compliance, observability, and operational resilience. Every engagement includes documented guardrails and measurable service levels.
Security & Trust
- Zero-trust architectures, SSO, and MFA
- Secrets management, key rotation, and audit trails
- Data encryption in transit and at rest
- Threat modeling, pentests, and secure SDLC
Governance & Compliance
- Data residency, retention, and lineage
- PII/PHI handling and consent workflows
- Policy-as-code and guardrails for AI systems
- Support for SOC 2, HIPAA, GDPR-aligned controls
Reliability & Support
- SLIs/SLOs for latency, uptime, and cost
- 24/7 on-call, incident response, and runbooks
- Chaos testing, failover drills, and DR strategies
- Progressive delivery, feature flags, and rollback plans
Governed delivery from day one
Security reviews, architecture decision records, and compliance checklists are part of our standard delivery. We align with your infosec process and ensure deployment paths meet organizational policies.
Products, Labs & Innovation
Accelerators, labs, and innovation for AI-native delivery
We invest in reusable assets and structured experiments so you move faster without sacrificing rigor. Labs outputs graduate into supported products with clear ownership and SLAs.
Productized Accelerators
Reference architectures, starter kits, and pre-built components to compress time-to-market.
- GenAI starter kits (RAG, evals, guardrails)
- Mobile AI experience templates (chat, voice, vision)
- Observability and FinOps dashboards for AI workloads
Labs & Experiments
Low-risk experimentation track for emerging models, modalities, and interfaces.
- Model bake-offs with evaluation harnesses
- Multimodal prototypes across voice, vision, docs
- Edge and offline AI trials with sync strategies
Innovation Sprints
2-4 week sprints to de-risk a hypothesis and turn it into a measurable artifact.
- Architecture spike with decision records
- Pilot deployment with logging and alerts
- Stakeholder demo and rollout plan
Reference implementations on demand
We maintain internal reference repos for chat, RAG, evaluations, mobile AI experiences, and observability. We adapt them to your stack (Azure, AWS, or GCP) with your security controls.
Insights & Thought Leadership
Points of view on building AI systems that last
We publish architecture blueprints, PoVs, and playbooks grounded in real delivery. Use them to guide platform strategy, not just prototypes.
PoV • Reliability & Safety
Operating GenAI in Production
Evals, guardrails, rollout strategies, and cost controls for enterprise LLM systems.
Request the full piece →Blueprint • Architecture
Architecture Patterns for AI-Native Apps
Reference topologies for mobile, web, and agentic systems with observability baked in.
Request the full piece →Guide • Data & Governance
Data Foundations for AI
Building vector pipelines, governance, and lineage so AI outputs are trustworthy.
Request the full piece →Playbook • Cost & Scale
FinOps for AI Workloads
Designing for cost predictability across training, fine-tuning, and inference.
Request the full piece →Use Cases & Solutions
Real engineering problems solved with AI-powered systems. Each solution demonstrates our approach: understand the problem deeply, design the right system architecture, and deliver measurable outcomes.
AI Copilots for Internal Teams
Problem
Enterprise teams struggle with information retrieval, repetitive tasks, and knowledge management across distributed systems.
System
Custom LLM-powered copilot with RAG over company documents, integrated with Slack/Teams, providing context-aware answers and automating workflows.
Outcome
60% reduction in support tickets, 40% faster onboarding, instant access to institutional knowledge for all team members.
Mobile Document Intelligence App
Problem
Field workers need to capture, process, and extract structured data from physical documents in real-time without connectivity.
System
React Native mobile app with on-device OCR, AI-powered document classification, offline processing, and cloud sync when connected.
Outcome
75% faster document processing, 90% accuracy in data extraction, works reliably in areas with poor connectivity.
GenAI-Powered Learning Platform
Problem
Educational content is static, not personalized, and learners have varying skill levels and learning preferences.
System
Adaptive learning platform with LLM-generated personalized content, AI tutoring, progress tracking, and interactive exercises.
Outcome
3x improvement in learner engagement, 50% faster skill acquisition, personalized learning paths for every user.
AI-Augmented Legacy System
Problem
Legacy ERP system has valuable data but poor UX, requiring extensive training and creating adoption barriers.
System
AI layer on top of legacy system providing natural language query interface, intelligent recommendations, and automated report generation.
Outcome
No disruption to existing operations, 80% reduction in training time, democratized access to business intelligence.
Data-Driven Decision Platform
Problem
Business teams rely on data analysts for insights, creating bottlenecks and delays in decision-making.
System
Self-service analytics platform with AI-powered insights, natural language queries, automated reporting, and predictive analytics.
Outcome
Self-service for 80% of analytics needs, 10x faster time-to-insight, proactive recommendations for business decisions.
Real-Time Fraud Detection System
Problem
Financial transactions need instant fraud analysis, but traditional rule-based systems have high false positive rates.
System
ML-powered fraud detection with real-time scoring, adaptive models, and explainable AI for audit trails and compliance.
Outcome
95% fraud detection accuracy, 70% reduction in false positives, sub-100ms response time for transaction scoring.
Your Use Case Not Listed?
These are representative examples. We engineer custom solutions for unique business problems across industries. Let's discuss your specific challenge.
Describe Your ChallengeEngagement Models
Engagement models and delivery maturity
Choose the model that fits your operating rhythm. Every model is backed by delivery governance, architecture reviews, and measurable SLOs.
Product Teams
Dedicated, cross-functional squads that own discovery, build, and operate AI-native products.
- Product + engineering leadership
- Roadmap, delivery, and SLO ownership
- Co-located rituals with your stakeholders
Co-Build with Your Teams
We embed with your engineers to accelerate delivery, upskill teams, and leave capabilities behind.
- Pairing, reviews, and shared repos
- Architecture decision records together
- Playbooks and runbooks handed over
Managed AI Platforms
We design, build, and operate the AI platform with SLAs, observability, and support.
- Platform SRE and on-call
- Evals, guardrails, and governance baked in
- Cost, latency, and reliability reporting
Delivery maturity path
Feasibility, architecture spikes, and ROI framing.
Production-like pilots with logging, alerts, and rollout plans.
Hardening, SLOs, chaos tests, and multi-region readiness.
Runbooks, incident response, model/eval refresh cycles, and FinOps.
Culture & Careers
A place for builders who want to shape the future of AI engineering
We hire engineers, product thinkers, and designers who love solving hard problems with rigor. If you care about shipping reliable AI systems and mentoring others, you will fit right in.
Engineering Craft
Code quality, testing, and documentation are table stakes. We invest in design reviews and retrospectives to keep raising the bar.
Research-Minded Builders
We translate AI research into production patterns, balancing experimentation with operational discipline.
Inclusive, Distributed Teams
Global teams working with clear rituals, transparent communication, and psychological safety to ship faster together.
Career Growth
Technical ladders, mentorship, and opportunities to own products, platforms, and open-source contributions.
Our long-term vision
- Be the most trusted AI-native engineering partner for enterprises globally.
- Advance the craft of operating AI systems responsibly at scale.
- Grow a community of engineers who blend research depth with delivery excellence.
Join the team
We are always looking for engineers, product managers, designers, and data specialists who want to build AI systems responsibly.
Send your resume to us at hr@arithmeticinfotech.com
Why Arithmetic Infotech
We are not a typical IT vendor. We are engineers who understand AI systems deeply and build production-grade software that lasts.
Engineering-First, Not Marketing-First
We are engineers who build production systems, not a marketing agency that outsources development. Technical depth and engineering quality are our foundation.
Deep GenAI + Backend Expertise
We understand LLMs, fine-tuning, RAG systems, and AI agents at a fundamental level. Combined with strong backend and data engineering skills.
Strong Data & Cloud Foundation
AI systems are only as good as their data and infrastructure. We build on solid data engineering and cloud-native architecture principles.
Experience with Production Systems
We have built and operated systems at scale. We know what it takes to go from prototype to production-grade, reliable software.
Long-Term Support Mindset
We build systems that are maintainable, documented, and designed for longevity. We support what we build and plan for evolution.
Transparent & Collaborative
Clear communication, regular updates, shared understanding of goals, and collaborative problem-solving throughout the engagement.
Traditional IT Vendor vs Arithmetic Infotech
| Aspect | Traditional IT Vendor | Arithmetic Infotech |
|---|---|---|
| Technical Depth | Surface-level understanding, relies on vendor solutions | Deep expertise in AI/ML, custom model development, system architecture |
| Engineering Approach | Marketing-led, outsourced development, template-based | Engineering-led, in-house expertise, custom solutions |
| AI Capabilities | Integrating third-party APIs, limited customization | Custom LLMs, fine-tuning, RAG systems, AI agent orchestration |
| Production Experience | Focus on demos and MVPs, limited production support | Production-grade systems, scalability, monitoring, long-term support |
| Data Engineering | Basic database work, limited data pipeline experience | Advanced data engineering, pipelines, feature stores, embeddings |
| Pricing Model | Fixed packages, opaque pricing, hidden costs | Transparent pricing, flexible engagement models, value-based |
Ready to work with a true engineering partner?
Start a ConversationAbout Arithmetic Infotech
A team of engineers focused on building intelligent, reliable, and scalable systems using modern AI and cloud technologies.
Arithmetic Infotech is an AI-native engineering company that designs and builds intelligent systems for forward-thinking organizations. We are not a traditional IT services company—we are engineers first.
Our expertise spans GenAI and LLM engineering, AI-powered mobile applications, cloud-native architectures, and data engineering. We build systems that combine the intelligence of modern AI with the reliability and scalability required for production environments.
We work with enterprise clients, product companies, and technology teams who need more than surface-level AI integration. Our engagements range from building custom LLMs and RAG systems to modernizing legacy applications with AI capabilities.
Based on engineering principles and technical depth, we deliver solutions that are secure, maintainable, and built to last. Our measure of success is not just project completion, but the long-term impact and operational reliability of the systems we create.
Our Engineering Values
Engineering Excellence
We write clean, maintainable code. We design scalable architectures. We test thoroughly. Engineering quality is non-negotiable.
Continuous Learning
AI and technology evolve rapidly. We stay current with research, frameworks, and best practices to deliver cutting-edge solutions.
Pragmatic Innovation
We use the right technology for the problem, not the newest technology. Innovation serves the business goal, not the other way around.
Long-Term Partnership
We build relationships, not just projects. Our success is measured by the long-term impact and reliability of the systems we create.
Our Team
We are a team of experienced engineers specializing in AI/ML, full-stack development, cloud infrastructure, and data engineering. Each team member brings deep technical expertise and a commitment to engineering excellence.
Our approach is collaborative, transparent, and focused on solving real engineering problems. We work as an extension of your team, bringing technical depth and execution capability to your most challenging projects.
Want to learn more about how we work?
Let's ConnectLet's Solve a Real Engineering Problem
Tell us about your technical challenge. We schedule discovery calls to explore architecture—no sales pitches, just engineering conversations.
Email us at
info@arithmeticinfotech.comWhat to Expect
- Response within 24 hours
- Technical discovery call
- Feasibility assessment and proposal
- Clear timeline and cost estimate
"Our goal is to understand your architecture before we ever discuss a contract."