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AI Automation & Systems Studio

AI agents, RAG, andautomation systemsfor real operations.

We build custom AI agents, RAG systems, workflow automations, and backend infrastructure for teams that want faster operations, clearer execution, and less manual work.

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10+ clients served in the past year · 3 active client partnerships

AI AgentsRAG SystemsData + Backend

sound familiar?

Broken systems breakeverything around them.

pain 01

Your team is drowningin manual work.

Copy-pasting between tools. Rebuilding reports every week. Processes that only work when the right person is in.

pain 02

Your stack is held togetherwith duct tape.

Airtable talks to Notion, Notion emails Slack, Slack triggers a Zap that breaks every Tuesday.

pain 03

You've tried tools.What you need is a system.

Zapier hits limits. Off-the-shelf SaaS doesn't fit. You need something built for how you actually operate.

the fix

That's exactlywhat we build.

What we build

Systems behind
modern AI operations.

We design connected AI systems that move knowledge, data, decisions, and actions through real business workflows.

01

Agents route decisions

Classification, routing, summarization, and workflow reasoning.

02

RAG retrieves evidence

Vector search, document Q&A, embeddings, and grounded responses.

03

Automations execute the work

Notifications, CRM updates, actions, webhooks, and process automation.

04

Data moves between systems

Scraping, APIs, databases, ETL, enrichment, and backend sync.

05

Tools give teams control

Dashboards, internal tools, admin systems, and operational views.

AI AgentsRAG SystemsData PipelinesInternal ToolsBackend Sync
Selected work

Systems shipped for
real business operations.

A few anonymized examples of AI, RAG, automation, and backend systems we've built across client work.

01
Secure AI Platform
Project record

Secure Enterprise Chatbot Platform

Secure internal document Q&A with Azure AD login, role-based access, citation-backed answers, chat history, and admin document workflows.

Archive note

Anonymized work sample from live client delivery.

Built with

Azure AD · RBAC · Document Q&A · Citations · Chat History

Azure ADRBACDocument Q&ACitationsChat History
02
Retrieval Engine
Project record

Hybrid RAG Retrieval Engine

A production-style retrieval engine using dense, sparse, and SPLADE retrieval, RRF fusion, reranking, LLM scoring, and FastAPI serving.

Built with

RAG · Pinecone · SPLADE · RRF · Reranking · FastAPI

RAGPineconeSPLADERRFRerankingFastAPI
03
Document AI
Project record

Mortgage Document AI Agent

Secure mortgage document Q&A with S3, Pinecone, LangChain RAG, GPT responses, PostgreSQL metadata, JWT auth, and audit-ready chat metrics.

Built with

FastAPI · LangChain · OpenAI · S3 · Pinecone · PostgreSQL · JWT

FastAPILangChainOpenAIS3PineconePostgreSQLJWT
10+Clients served
3Active partnerships
1yrFocused delivery
FullAI · RAG · Data · Backend

How we work

A process built forexecution, not meetings.

Four stages. Clear deliverables at each step. No surprises.

scroll to explore

→
01

Step 01

Audit

We map your current operations — tools, workflows, handoffs, and bottlenecks. You get a clear picture of where time is being lost.

Discovery · Mapping · Analysis

02

Step 02

Design

We architect the solution before writing a line of code. System diagrams, data models, integration maps. You approve before we build.

Architecture · Diagrams · Approval

03

Step 03

Build

Focused sprints with weekly check-ins. You see progress at every stage, not just at the end. No black-box development.

Engineering · Sprints · Delivery

04

Step 04

Deploy & Iterate

We deploy, train your team, monitor for 30 days, and iterate based on real usage. Most clients see ROI within 60 days.

Launch · Training · Monitoring

Ready to fix your operations?

Let's build somethingthat actually works.

Email us your biggest workflow problem and we'll tell you whether it needs an AI agent, a RAG workflow, or a cleaner automation system — no pitch deck, no fluff.