AI & Engineering
Enterprise Autonomous AI Agents & Intelligent Pipelines
Transform unstructured enterprise data into real-time autonomous agentic workflows with custom LLMs, vector search, and strict security compliance.
Highlights
AI & ML Systems, done properly.
- 90% reduction in manual data processing time
- Instant contextual answers across millions of documents
- Zero data leak security compliance with VPC deployment
Overview
What you get.
Technier designs and deploys production-grade Autonomous AI Agents, Retrieval-Augmented Generation (RAG) architectures, and LLM fine-tuning solutions engineered to run reliably at scale.
Our AI engineering team specializes in building robust Agentic workflows using LangChain, LlamaIndex, OpenAI, and open-source models. We combine vector databases (Pinecone, Qdrant, PGVector) with real-time streaming data to automate complex reasoning tasks.
Capabilities
Key features and capabilities.
Multi-agent collaborative reasoning workflows
Hybrid RAG with dense and sparse vector retrieval
Fine-tuned open source LLMs (Llama 3, Mistral)
Enterprise guardrails, toxicity filtering & audit logs
Seamless API integration with existing cloud ERPs
Stack
Technologies we use.
- Python
- FastAPI
- PyTorch
- LangChain
- Pinecone
- OpenAI API
- Docker
Methodology
How we deliver AI & ML Systems.
01
Data Architecture Audit
We evaluate your raw data sources, schema requirements, and security compliance constraints.
02
RAG & Agent Prototyping
We construct custom embedding pipelines and benchmark agent reasoning performance.
03
Enterprise Cloud Deployment
We deploy isolated VPC agent clusters with automated monitoring and failover.
FAQ
Questions about AI & ML Systems.
Can AI agents integrate with our internal SQL database?
Yes, our agentic workflows connect securely to PostgreSQL, Snowflake, MySQL, and REST APIs.
Is our proprietary company data safe?
Absolustely. We deploy self-hosted or zero-data-retention models inside your dedicated AWS/GCP VPC.
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Have a product in mind? Let's talk.
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