AI Build & Implementation
AI agents that handle real work — end to end.
We design, build, and deploy multi-tool AI agents that reason, take actions, and handle complex workflows autonomously — from customer support to operations to growth.
~65%
Avg. ticket reduction
4–6wk
Typical delivery
5+
Tools per agent
// what_it_is
What is AI Agents & Agentic Systems?
An AI agent is a system that can reason about a task, decide which tools to use, execute them, observe the results, and keep going until the job is done — without a human in the loop for every step. Unlike a simple chatbot, an agent takes actions.
// the_problem
Does this sound familiar?
Customer support eating your team's time. Repetitive queries, order tracking, onboarding questions — an agent handles these autonomously, 24/7.
Manual workflows that should be automated. Any process where someone follows a checklist, queries a system, and produces an output is a candidate for an agent.
No bandwidth to build it yourself. You know AI could help — but scoping, building, and deploying it isn't your team's job. It's ours.
Tried off-the-shelf tools, didn't fit. Generic AI products rarely match your specific workflows. We build for your data, your systems, your edge cases.
// what_we_build
What we deliver
01
Multi-tool agentic systems
Agents with 3–10 specialized tools that Claude reasons across — calling the right one for each request.
02
Customer support agents
Handles inbound queries, looks up order data, escalates intelligently. Reduces ticket volume by 50–70%.
03
Operations automation agents
Monitors data, triggers actions, generates reports — running on a schedule or responding to events.
04
Onboarding & intake agents
Guides new users or clients through setup, collects information, and kicks off downstream workflows.
05
Internal knowledge agents
Searches your docs, databases, or CRM to answer team questions without digging through five tools.
// how_it_works
How we work
1
Discovery
We map the workflow, identify the tools needed, and define what success looks like — before writing a line of code.
2
Tool design
Each tool is designed with a precise JSON schema that Claude uses to reason about when and how to call it.
3
Build & test
We build the agent, run it against real scenarios, tune the system prompt, and iterate until it handles edge cases cleanly.
4
Deploy & hand off
Deployed to Vercel or your stack with a secure API proxy, full documentation, and a handoff session.
// tech_stack
Technology we use
AI Model
Claude Sonnet / Opus
API Layer
Anthropic Tool Use
Backend
Node.js / Python
Frontend
React / Next.js
Hosting
Vercel / AWS
Security
Env var proxy
// related_work