Comprehensive AI solutions from strategy to deployment
We design and build AI-native platforms with retrieval-augmented generation systems.
This includes end-to-end platform re-architecture, RAG pipeline design for contextual intelligence, agent-driven decision systems, and full-stack delivery. We structure thousands of use cases, generate contextual playbooks, and optimize for rapid iteration cycles.
For: SMEs adopting AI, SaaS platforms adding intelligence, teams building decision support systems.
Outcomes: 10× faster output generation, 30%+ engagement increases, production-ready platforms in ~2 months, 6,000+ structured use cases.
We build autonomous systems that execute multi-step workflows with minimal human intervention.
This includes designing agentic workflows for reconciliation, event-driven orchestration for exception handling, workflow automation for operations, and intelligent routing systems. We create agents with clear boundaries, human checkpoints, and audit trails.
For: Fintech teams reducing manual work, operations teams scaling processes, enterprises automating workflows.
Outcomes: ~70% reduction in manual workload, deployment times from hours to minutes, ~30% productivity improvements.
We build platforms for generating synthetic training data for computer vision models.
This includes web-based synthetic data generation platforms, real-time event-driven backends, Python-based CV workflow integration, hybrid deployment support (on-prem + cloud), and full observability for performance tracking.
For: Teams training CV models, organizations requiring consistent data generation, enterprises with hybrid infrastructure needs.
Outcomes: Production-ready platforms in <6 months, faster model iteration, support for both on-prem and cloud environments.
We design observability layers that provide visibility into AI agent reasoning and performance.
This includes cognitive observability tooling for agent ecosystems, analysis of decision quality and prompt effectiveness, failure and retry pattern detection, and extensible open architectures for reusability.
For: Teams managing complex AI agents, organizations requiring governance, platforms needing debugging capabilities.
Outcomes: Deeper agent behavior insights, improved debugging, enhanced governance, open reusable frameworks.
We build platforms for managing industrial device fleets with edge and cloud orchestration.
This includes end-to-end edge-to-cloud platform design, real-time device communication and control, cloud-based centralized management workflows, secure authentication and role-based access, and offline fleet management capabilities.
For: Manufacturing teams managing device fleets, IoT product companies, enterprises requiring hybrid infrastructure.
Outcomes: Commercial device launches, 15% adoption increases, ~$50K annual cost savings, offline management in <3 months.
We build modular testing frameworks for AI safety, robustness, and governance compliance.
This includes modular testing plugins for AI evaluation, LLM safety and robustness testing, data governance validation, and alignment with international AI governance standards. We deliver reusable, extensible testing components.
For: Organizations validating AI systems, teams requiring compliance, platforms needing safety assurance.
Outcomes: Consistent AI validation, industry-aligned governance practices, reusable testing components.
We modernize application architecture and deployment pipelines for AI systems.
This includes CI/CD pipeline modernization, infrastructure as code implementation, deployment automation, and event-driven architecture design. We reduce deployment friction and improve team productivity.
For: Teams with slow deployment cycles, organizations modernizing infrastructure, platforms scaling operations.
Outcomes: Deployment times from hours to minutes, improved engineering productivity, reduced operational overhead.