Artificial Intelligence

Turn your data into
intelligent action.

We bridge the gap between foundation models and your business reality. From RAG pipelines to autonomous agents, we engineer production-grade AI systems.

Start AI InitiativeView AI Case Studies
Zaproo AI Agent
Analyze Q3 sales data and identifying top 3 churn risks.
Querying PostgreSQL...
Running Isolation Forest Model...

I've analyzed 14,200 records. Here are the top risks:

Acme Corp92% Risk
Global Tech78% Risk
Knowledge Base
Privacy Guard
PII Redacted

RAG & Knowledge Bases

We connect LLMs to your private data (PDFs, SQL, Notion) using Vector Databases. Your AI answers questions based on your truth, not hallucinations.

Autonomous Agents

Deploy intelligent agents that can browse the web, use APIs, and execute complex multi-step workflows to automate customer support and operations.

Model Fine-Tuning

When prompt engineering isn't enough. We fine-tune open weights models (Llama 3, Mistral) on your specific domain data for superior performance and privacy.

Semantic Search

Context-aware
intelligence.

Chatbots that guess are liabilities. We engineer semantic search pipelines that retrieve the exact paragraphs from your documentation needed to answer a query, ensuring high accuracy and citability.

Private Data Security (SOC 2)
Low-latency Vector Retrieval
Scalable Inference API
rag_pipeline.py
Ln 14, Col 32
1import openai
2from vector_store import Pinecone
3
4async def query_knowledge_base(query: str):
5# Generate embedding for the user query
6embedding = await openai.Embedding.create(
7input=query,
8model="text-embedding-3-large"
9)
10
11# Retrieve context from private vector store
12context = db.similarity_search(
13vector=embedding.data[0].embedding,
14top_k=5
15)
16
17# Synthesize answer with source attribution
18return llm.generate(
19prompt=build_rag_prompt(query, context),
20temperature=0.2
21)
Terminal
$ node pipeline.js --query "Return policy?"
-> Generating embeddings...
-> Retrieved 3 documents from 'policies' index.
Answer: According to document #142, returns are accepted within 30 days if the item is unworn...
Done (0.8s)_

The AI Stack

We engineer model-agnostic systems using top-tier foundation models (OpenAI, DeepSeek) and modern JavaScript frameworks to ensure scalability and vendor independence.

Frontier ModelsOpenAI & DeepSeek
Private AILlama 3 & Mistral
App FrameworksNext.js & React
Backend & EdgeNode.js & PHP/Laravel
Vector SearchPinecone & Weaviate
InfrastructureDocker & AWS
Methodology

From Proof of Concept to Production.

AI projects often stall at the demo stage. We apply rigorous engineering practices to ensure your models are reliable, cost-effective, and secure in production.

Our Safety Standards
1

Data Audit & Privacy

We sanitize and structure your data, establishing strict PII redaction protocols before training begins.

2

Model Selection

We benchmark GPT-4, Claude, and Llama 3 against your specific use cases to find the best cost/performance ratio.

3

Eval & Fine-Tuning

We build automated evaluation pipelines (LLM-as-a-judge) to measure accuracy and prevent regression.

4

Deployment

Containerized inference endpoints with rate-limiting, caching, and fallback mechanisms for high availability.

Ready to automate?

Our AI engineers are ready to assess your data readiness and build your first proof of concept.

Book a Strategy Session
Turn your data into intelligent action. | Zaproo