person
"Analyze market trends"
smart_toy
database
RAG
code
Code
search
Search
api
API
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GPT-44 tools
System Status: Operational

Architecting
Autonomous
Intelligence.

End-to-end development of production-grade LLM pipelines and Agentic workflows. From prototype to scalable MLOps infrastructure.

99.9%Uptime
<25msLatency
100M+Vectors
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The Architecture

Visualizing the flow from raw data to autonomous action through high-performance vector retrieval and LLM reasoning.

01
database

Ingestion

Unstructured data parsing & chunking pipelines.

02
grid_view

Embedding

High-dimensional vectorization & storage.

03
psychology

Reasoning

Context-aware inference via LLMs (Llama 3, GPT-4).

04
smart_toy

Agent Action

Multi-step planning & autonomous tool execution.

05
output

Response

Structured output delivery via secure API endpoints.

Core Capabilities

hub

Agentic Orchestration

Design and deployment of autonomous agents capable of complex reasoning. Utilizing LangChain and AutoGen to create systems that can browse the web, execute code, and manage state across long-running tasks.

Multi-AgentReAct PatternTool Use
search

Advanced RAG

Hybrid search implementation combining sparse and dense vectors. Custom reranking models to boost retrieval accuracy by 40%+.

ACCURACY METRIC+42%
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Enterprise MLOps

Secure deployment within VPCs using Docker & Kubernetes. Comprehensive monitoring with Prometheus & Grafana.

check_circleCI/CD Pipelines
check_circleModel Versioning
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Fine-Tuning & Quantization

Adapting open-source models (Llama 3, Mistral) to your specific domain using LoRA/QLoRA. Reducing VRAM usage by up to 60% without significant performance loss.

MODEL_SIZEFP16 → INT4
VRAM_USAGE-65%
THROUGHPUT2.4x
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TensorFlowHuggingFaceLangChainLlamaIndexPineconeDockerKubernetesPyTorchOpenAIAnthropic
TensorFlowHuggingFaceLangChainLlamaIndexPineconeDockerKubernetesPyTorchOpenAIAnthropic

Ready to deploy intelligence?

Let's discuss how we can integrate state-of-the-art GenAI into your product stack with enterprise-grade reliability.