// AI agent development
AI Agent Development Singapore
Custom AI Agents Built for Your Business — Not Just Another Chatbot
Your competitors are still using chatbots. We build AI agents — systems that actually think, plan, and act autonomously on your behalf. From lead qualification agents to internal knowledge workers to fully automated content pipelines, we design and ship production-grade AI agents that plug directly into your existing stack.
30+
AI Agents Shipped
$50/hr
Avg Cost Saved Per Agent
6 wks
Avg Time to Production
1M+
Agent Actions Logged
// why automate
What You Actually Gain
Save 20+ Hours a Week
Agents handle repetitive research, drafting, qualification, and data entry around the clock — so your team focuses on work that actually needs a human.
Scale Without Hiring
One agent can do the work of multiple staff at a fraction of the cost. Process thousands of leads, documents, or tasks simultaneously with no additional headcount.
Respond in Seconds, Not Days
AI agents qualify leads, answer questions, and trigger follow-ups the moment someone reaches out — before competitors even see the notification.
Cut Operational Costs
Automate the work that currently drains your team's time. Our clients typically recover the development cost within 3–4 months through labour and tooling savings.
Smarter Than a Chatbot
Unlike scripted chatbots, AI agents reason, retrieve context, use your actual tools, and make decisions — adapting to situations they've never seen before.
Plugs Into Your Existing Stack
Agents connect to your CRM, calendar, email, Slack, databases, and APIs. No rip-and-replace — your agent works inside the tools your team already uses.
// technology
Our Technology Stack
Core Stack
Also in Our Stack
// what we build
Our Ai Agent Development Services
Custom AI Agent Development
End-to-end design and build of single or multi-agent systems — from scoping the agent's reasoning loop to shipping to production with monitoring.
Multi-Agent Orchestration
LangGraph and MCP-based pipelines where specialised agents hand off tasks, verify each other's outputs, and escalate edge cases to a human in the loop.
RAG & Knowledge Base Integration
Connect your agent to internal documents, databases, and APIs. Your agent knows your product, your policies, and your customers — not just the internet.
Agent-to-Tool Integrations
Hook agents into your CRM, Slack, email, calendars, databases, and third-party APIs. Agents that can read and write to your actual systems.
Monitoring & Evaluation
Production observability — trace every agent decision, catch hallucinations, measure task completion rates, and continuously improve agent behaviour.
Agent Maintenance & Iteration
Ongoing support, model upgrades, prompt engineering as LLMs improve, and feature expansions as your use case grows.
// how we work
Our Proven Process
Step 1
Discovery & Scoping
- Map the exact workflow the agent will own or assist
- Identify data sources, tools, and systems the agent needs access to
- Define success metrics — task completion rate, time saved, error rate
- Agree on human-in-the-loop checkpoints and escalation rules
Step 2
Agent Design
- Architect the reasoning loop: perceive → plan → act → reflect
- Select models per sub-task (Claude for reasoning, lighter models for extraction)
- Design tool schemas and MCP integrations
- Write and iterate on system prompts with evaluation sets
Step 3
Build & Integrate
- Implement agent logic in Python with LangGraph orchestration
- Connect to your APIs, databases, and communication channels
- Build admin interface or monitoring dashboard as needed
- Set up LangSmith tracing so every decision is logged
Step 4
Evaluation & Red-Teaming
- Run agent against 100+ real-world test cases
- Adversarially probe for hallucinations and edge cases
- Tune prompts and guardrails based on failure modes
- Validate cost-per-run and latency against targets
Step 5
Deploy & Handover
- Production deployment on your infrastructure or ours
- Monitoring alerts and weekly performance reports
- Team training and runbook documentation
- 30-day post-launch support included
// why us
Why Choose Power Digital?
First Movers in SG
Building production AI agents in Singapore since 2024 — before most agencies knew what MCP was
We Run Agents Ourselves
Our own SEO pipeline, content agents, and puzzle generators run in production — we eat our own cooking
No Chatbot Upsells
We don't repackage ChatGPT with a UI. Every agent is purpose-built for your specific workflow
Full-Stack Delivery
From LLM prompt engineering to the frontend your users see — one team, one accountability
Production-Proven Stack
Claude API + LangGraph + MCP — the stack top AI labs use internally
Transparent Pricing
Fixed-scope projects with milestone payments. No open-ended retainers without clear deliverables
// faq
Frequently Asked Questions
Ready to Put AI to Work in Your Business?
Book a free 30-minute scoping call. We'll map the workflow, estimate the build, and tell you honestly whether an agent is the right solution — or whether something simpler would work better.
// AI agent development
Insights & Resources
AI Agent Development
How We Built an AI Puzzle Platform Targeting 162K Monthly Searches
21 Jun 2026
AI Agent Development
Model Context Protocol (MCP) Explained
19 Jan 2026
AI Agent Development
Multi-Agent Systems Explained — When One AI Isn't Enough
14 Jan 2026
AI Agent Development
LangGraph Tutorial — Build Multi-Step AI Agents with State Management
10 Jan 2026