Build & Integrate Production Systems
Engineer applications, APIs, services, AI capabilities, data pipelines, and integrations within your existing technology environment.
Smaitic Labs technology expertise
Smaitic Labs works across modern technology ecosystems for AI engineering, software and product engineering, platform engineering, cloud infrastructure, DevOps, data engineering, observability, security, and software architecture. With 10+ years of engineering experience and 50+ engineering projects delivered, Smaitic Labs helps organizations select and apply technology based on workload, performance, scale, security, operational complexity, and cost. The Tech Stack page covers LLMs, AI agents, RAG, vector databases, MLOps, frontend and backend frameworks, cloud platforms, containers, Infrastructure as Code, databases, data platforms, DevOps, observability, identity, and security. Smaitic adapts to each client's existing technology environment instead of forcing one preferred stack. Engineering experience with Avesha, Ohai.ai, WISP Ecosystem, Vanidya, and NeuroRetail.
Common questions
What technologies does Smaitic Labs work with?
Smaitic Labs works across AI and machine learning technologies, LLM and retrieval systems, cloud platforms, containers, infrastructure as code, frontend and backend frameworks, mobile engineering, databases, data engineering, DevOps, observability, security, and architecture practices.
Does Smaitic Labs support AI and machine learning technology stacks?
Yes. Smaitic Labs supports LLM applications, agentic AI frameworks, retrieval techniques, vector databases, indexing and search, machine learning frameworks, MLOps, and AI engineering platforms.
Does Smaitic Labs work with existing client technology stacks?
Yes. Smaitic Labs integrates with existing client technology ecosystems and recommends technologies based on architecture, scalability, engineering maturity, and long-term business goals.
What is included in Smaitic Labs' AI technology stack?
Smaitic Labs' AI technology stack includes LLMs, AI agent frameworks, RAG and retrieval systems, vector databases, semantic search, AI platforms, MLOps, model operations, and AI infrastructure.
What engineering practices does Smaitic Labs bring?
Smaitic Labs brings modern engineering practices across cloud-native development, DevOps automation, platform reliability, observability, security, architecture reviews, engineering design, testing, and quality engineering.
Technology Stack
Technology Expertise Across AI, Software, Data & Cloud
We work across modern AI, software, data, cloud, and infrastructure technologies, selecting the right stack for workload, performance, security, scale, and cost while integrating with your existing environment.
Engineer Architecture Around the Workload & Scale
We select architecture and technologies based on workload, performance, scale, security, operational complexity, and cost, not technology preference. Every decision considers how the system needs to perform, operate, and evolve in production.
Workload-Driven Architecture
Choose architecture and infrastructure based on how the system actually behaves, not what's currently popular.
Performance & Cost Economics
Evaluate throughput, utilization, scalability, and operating costs together rather than optimizing them independently.
Security & Reliability By Design
Build identity, access, infrastructure security, observability, resilience, and operational controls into the technology foundation.
Fit With Your Engineering Ecosystem
Work within existing architecture, repositories, cloud environments, standards, tooling, and engineering practices wherever appropriate.
Our Technology Expertise
Our engineers work across the technologies required to build, scale, modernize, secure, and operate production systems. The stack below represents our core expertise and continues to evolve with the systems and engineering environments we work within.
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AI & ML
1 expertise domains
expertise.map
Artificial Intelligence & Machine Learning
AI Engineering, LLMs, Agents & MLOps
LLMs & Models
OpenAIAnthropic ClaudeGoogle GeminiHugging Face
AI Agents & Orchestration
LangChainLlamaIndexCrewAIAutoGen
RAG, Retrieval & Search
RAGVector RetrievalSemantic SearchPineconepgvectorElasticsearchOpenSearch
AI Platforms & MLOps
Amazon BedrockAzure OpenAIGoogle AI StudioMLflowKubeflow
AI Engineering, LLMs, Agents & MLOps
LLMs & Models
OpenAIAnthropic ClaudeGoogle GeminiHugging Face
AI Agents & Orchestration
LangChainLlamaIndexCrewAIAutoGen
RAG, Retrieval & Search
RAGVector RetrievalSemantic SearchPineconepgvectorElasticsearchOpenSearch
AI Platforms & MLOps
Amazon BedrockAzure OpenAIGoogle AI StudioMLflowKubeflow
Beyond the Technology Stack
Engineering Production-Ready SystemsFrom Architecture to Operations
Our expertise extends beyond individual technologies. We engineer across application, AI, data, cloud, and infrastructure layers to build, integrate, modernize, and operate production systems.
Modernize Applications & Platforms
Evolve legacy applications, architecture, infrastructure, and dependencies to improve scalability, maintainability, performance, and development velocity.
Productionize AI & Data Workloads
Integrate LLMs, RAG, AI agents, machine learning, and data workflows with production applications, APIs, infrastructure, security, and MLOps.
Operate & Optimize Cloud Infrastructure
Automate deployments, strengthen observability and reliability, optimize infrastructure utilization, and improve production operations across cloud environments.
