How long does it take to build a custom AI agent?

Most AI agent projects at WNC take 4 to 12 weeks depending on integrations, data complexity, and the evaluation harness required for production readiness.

How much does it cost to build a custom AI agent?

WNC AI agent projects typically range from $15,000 for a focused single-purpose agent to $150,000 for a multi-agent system with custom tooling, integrations, and evaluation infrastructure.

Which LLM providers does WNC support?

WNC primarily uses Anthropic Claude and OpenAI GPT models. Other providers (Gemini, open-source models on AWS Bedrock or Together AI) are supported on request.

Can the AI agent integrate with our existing systems?

Yes. WNC builds custom integrations with CRMs, helpdesks, databases, internal APIs, and SaaS tools as part of standard delivery.

How do you evaluate AI agent quality before deployment?

Every WNC AI agent ships with an evaluation harness — a curated test set of input/expected-output pairs that runs on every change and is used to gate releases.

Does WNC handle deployment and ongoing maintenance?

Yes. WNC deploys agents to client-owned cloud (typically AWS) and offers ongoing maintenance and iteration as a separate engagement.

All services

AI agents & chatbots

Serve every customer instantly, without adding headcount.

Faster answers, more capacity, lower cost to serve.

Your team is buried under repetitive questions and tasks that pull them off the work that actually matters. We build AI agents that handle those conversations and tasks the way your best people would — so customers get answers in seconds, your team gets its focus back, and service quality holds as you grow.

Let’s manage Open Kanban

01 / What it solves

Where the pressure comes off.

Customers never wait for an answer

Routine questions get resolved in seconds, at any hour — your team only steps in when it genuinely needs to.

Answers from your data in plain words

Ask in plain language and get the summary or number you need, without waiting on an analyst.

The busywork handles itself

Repetitive, multi-step tasks get done on their own, so people spend their time on work that needs a human.

Everyone finds the right answer fast

Your team and your customers get accurate answers pulled straight from your own documents and systems.

02 / Stack

The technology we build with.

Industry-standard, boring in the good way: tools with a future, that the next engineer will know too.

LLM Providers

OpenAI GPT-4
Advanced reasoning and conversation
Claude (Anthropic)
Safe, helpful AI assistant
Google Gemini
Multimodal AI capabilities
Llama/Mistral
Open-source model deployment

Agent Frameworks

LangChain
Framework for LLM application development
LangGraph
Stateful multi-actor agent orchestration
CrewAI
Multi-agent collaboration framework
AutoGen
Microsoft’s multi-agent framework

Integration & Tools

MCP Protocol
Model Context Protocol for tool integration
Function Calling
Native LLM tool use capabilities
Vector Databases
Pinecone, Weaviate, Qdrant
APIs & Webhooks
Connect to any external service

03 / Approach

How we build things that last.

Context-Aware

Agents that understand your business domain and context.

Real-Time Response

Fast, efficient processing for instant user interactions.

Safe & Controlled

Guardrails, content filtering, and human-in-the-loop options.

Multi-Agent Systems

Coordinated agents working together on complex tasks.

04 / Standards

Best practices we don’t skip.

We adhere to industry standards and proven methods on every project — they are what makes the estimate hold.

Prompt engineering and optimization
Context window management
Token cost optimization
Fallback and error handling
Response validation and filtering
Conversation memory management
A/B testing for prompts
Monitoring and analytics
Rate limiting and throttling
Security and data privacy

05 / Infrastructure

Where it runs, and how it stays up.

AWS — ECS, Lambda & Step Functions for agent runtimes
NVIDIA GPU inference for self-hosted models
Vector stores (pgvector, Pinecone) for retrieval & memory
Full observability: tracing, eval harness, cost & token dashboards

Start

Ready to build your AI agent?

Tell us what it has to do. A senior engineer writes back with an honest scope and price.

Let’s manage or open the client Kanban

Serve every customer instantly, without adding headcount.

Faster answers, more capacity, lower cost to serve.