Production-grade AI systems, not prototypes.
AI-first software engineering for production systems
We design and build AI-enabled platforms, data systems, and backend services that ship fast, scale reliably, and deliver measurable business impact.
What teams hire us for
- AI integrated into real workflows (not demo apps)
- Backend and data foundations that scale cleanly
- Measurable quality and reliability via evaluation + observability
- Clear delivery milestones and documentation
Measured Outcomes - Time Saved, Accuracy Gains, Faster Response Times, Higher Adoption.
Outcomes, not just deliverables
We align delivery to measurable metrics: time saved, accuracy improvements, latency, adoption, and operational reliability.
Web Applications
Design and build modern web apps that are fast, secure, and user-focused.
Workflow Automation
Reduce manual effort with AI-assisted validation, routing, and decisioning.
Knowledge Retrieval
Enable fast, grounded answers across documents, policies, and internal knowledge.
Search and Discovery
Improve relevance and findability across large datasets and catalogs.
Operational Intelligence
Build data pipelines and analytics that drive real decisions.
Platform Reliability
Production-grade APIs and services designed for scale and maintainability.
Services
AI Engineering, backend platforms, data/search foundations, and cloud delivery—with a delivery model built for speed and correctness.
AI Engineering
- RAG assistants and internal copilots
- Agentic workflows integrated with your tools and systems
- Model orchestration for multi-step AI workflows
- Traditional ML models for prediction, classification, and optimization
- LLM fine-tuning for domain-specific performance
Backend and Platform Engineering
- CRM and ERP software built for your workflows
- API platforms with versioning, auth, and predictable contracts
- Performance, caching, and concurrency aligned to real traffic
- System redesign and modernization with clear milestones
Data Engineering, Analytics and Search
- ETL/ELT pipelines with validation and reliability patterns
- Search indexing, relevance tuning, and retrieval layers
- Dashboards for analytics and decision-making
- Curated datasets for BI, analytics, and downstream ML
- Data quality, lineage and anomaly detection
Cloud and Deployment
- Containerized deployments and CI/CD foundations
- Environment strategy and release discipline
- Observability with logs, metrics, tracing, and alerting
- Security baseline with secrets management and least privilege
- Secure, cost-aware scaling
A delivery model built for speed and correctness
We prioritize shipping early in thin slices while maintaining production engineering standards.
Discover
01Goals, constraints, risks, success metrics, and system boundaries.
Design
02Architecture, data contracts, evaluation plan, and rollout strategy.
Build
03Iterative delivery with clear milestones and review points.
Operate
04Monitoring, quality evaluation, and continuous improvement.
Engagement models
Make it easy to buy. Clear scope, clear outcomes, and a delivery rhythm you can trust.
Discovery Sprint (1–2 weeks)
Scope, architecture, plan, and pilot definition.
- Success metrics and constraints
- Architecture + evaluation plan
- Delivery roadmap and risks
Build and Launch (4–10 weeks)
Implement MVP, deploy, instrumentation, handover.
- Thin-slice delivery with milestones
- Production deployment + observability
- Documentation and handover
Retainer / Growth
Ongoing improvements, features, operational excellence.
- Continuous enhancements and optimization
- Quality monitoring and regression checks
- Roadmap execution support
Built by engineers from strong institutions and delivery environments
About us
We build AI-first software that ships and scales. We are a small, engineering team focused on building reliable AI-enabled products and platforms, especially where AI must operate inside real systems: data pipelines, search, workflows, and customer-facing applications.
Our approach is outcome-driven: ship production-grade systems quickly, measure impact, and continuously improve.
Our vision
AI should not live in prototypes. It should be an operational capability that is secure, observable, and continuously improving. We help teams move from "AI ideas" to "AI running in production" with strong engineering fundamentals, clear constraints, and measurable quality.
Education & Industry Background
Education
- Indian Institute of Technology (IIT), Madras
- Aligarh Muslim University (AMU)
- Nottingham Trent University, UK
Industry experience
Experience across product and enterprise organizations, including:
What clients typically value
Clear communication
Direct updates, explicit tradeoffs, and accountable ownership.
Fast iteration with standards
Thin-slice delivery without sacrificing engineering rigor.
System thinking and documentation
Interfaces, risks, and operational realities documented early.
Production reliability
Observability, monitoring, and graceful failure patterns from day one.
Security and data handling
Access control, auditability, and privacy-aware system design.
Measured impact
Outcomes tied to metrics like time saved, accuracy, latency, and adoption.
Let’s build something reliable, measurable, and production-ready
Tell us your goal and constraints. We’ll propose a clear path from discovery to deployment.
Typical start
Discovery sprint → plan → pilot definition.
Delivery style
Thin slices, measurable milestones, production standards.
Success metrics
Time saved, accuracy, latency, adoption, reliability.