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AI Product Engineering

Integrating LLMs, computer vision, and predictive analytics into production-ready workflows.

Frameworks & Tools

Gemini 2.5/3.0LangChainPineconePyTorchFastAPI

Key Benefits

  • Personalized User Experiences
  • Automated Content Generation
  • Predictive Business Insights

Our Approach

01

RAG Implementation

Connecting LLMs to your private data for grounded, accurate responses.

02

Prompt Engineering

Specialized optimization to reduce hallucinations and token costs.

03

Agentic Workflows

Building autonomous agents that perform multi-step business tasks.

Key Deliverables

Custom AI Models/Pipelines

Fine-tuned LLMs or bespoke computer vision models.

Integration API

Secure endpoints to connect AI capabilities to your existing app.

Evaluation Framework

Tools to monitor AI accuracy, latency, and costs.

Typical Timeline

Weeks 1-3

Feasibility & Prototyping

Data assessment, prompt engineering, and initial proof-of-concept.

Weeks 4-8

Pipeline Engineering

Building RAG systems, model fine-tuning, and robust APIs.

Weeks 9-10

Integration & Monitoring

Connecting to frontend apps and setting up cost/performance tracking.

Service FAQ

Absolutely. We ensure enterprise-grade security and do not train public models on your private data.

We use a combination of OpenAI, Anthropic, Gemini, and open-source models depending on your needs.