Quick Win
One integration or one automated workflow. A single API connection or a single notification pipeline.
From $400
1 week
All services
Service 03
AI AUTOMATION & API INTEGRATION
AI Automation & API Integration
AI is most useful when it can work with the systems and information your business already depends on.
We build AI assistants, AI agents, and API integrations around your actual workflows. That can mean a read-only assistant over stock and pricing, an AI-native workflow connected through MCP, or an agent that monitors data and takes approved actions.
What We Build
We connect models such as Claude, OpenAI, and Gemini to approved business data and tools. The result is not a generic chatbot: it is an assistant or agent with a defined job, controlled access, useful context, and a clear boundary around what it can do.
AI-First Capabilities
AI assistants and agents come first. API integrations provide the reliable connections that make them useful inside your business.
- AI assistants over business data, documents, stock, pricing, customers, and ledgers
- AI agents for defined actions such as monitoring, flagging, drafting, and routing
- MCP tool connections that let assistants use approved business capabilities
- Claude, OpenAI, Gemini, and other model-provider integrations where they fit the use case
- Retrieval and search over private company information
- Human approval, permissions, guardrails, and auditability for consequential actions
- API integrations, data synchronization, notifications, and workflow automation
- Monitoring and error handling so agent and integration failures do not stay hidden
Common AI & API Patterns
AI Assistant over Business Data
Let staff ask plain-language questions over one or more approved data sources, such as stock, pricing, customer history, suppliers, or ledgers.
AI Agent with Approved Actions
Give an agent a defined role: monitor records, flag accounts, draft replies, or route requests while keeping permissions and human approval explicit.
MCP & API Connections
Connect a model to the tools and APIs it is allowed to use so the workflow is grounded in current business data rather than generic answers.
CRM ↔ ERP Sync
Keep customer, order, and account information aligned between business systems and make the connected data available to the right workflow.
Notifications & Data Pipelines
Trigger email, SMS, reports, or internal actions when a business event occurs, with logs and failure handling built in.
Pricing
These are starting prices for clearly defined scopes. The final price depends on the systems involved, data access, model choice, permissions, testing, and hosting requirements.
API Integrations
Growth
Multi-system sync. CRM to ERP, several webhooks, or a data pipeline with reporting built in.
From $2,000
3 to 5 weeks
AI Automation & AI Agents
AI Assistant (Starter)
Answers plain-language questions over one data source, like stock and pricing, or a single customer list. A real, working assistant, just narrower in scope than the full case study below.
From $650
1 to 2 weeks
AI Assistant (Full)
Connected across your systems the way the spare parts assistant below is: customer history, stock, pricing, suppliers, and ledgers in one place.
From $2,800
3 to 5 weeks
AI Agent
An agent that takes action on its own: monitoring data, flagging accounts, drafting replies, or routing requests without a person doing it manually.
From $4,500
6 to 10 weeks
Full AI Automation Platform
Several agents and workflows connected together across different parts of your business.
Custom quote, typically from $12,000
10+ weeks
Not sure yet how big the job is? We also offer hourly work at $40 to $50 an hour for automation and AI work where scope is not fully clear until we are inside your systems. Once we understand the shape of the problem, we can usually move you to a fixed price.
Our AI Automation Process
01
Find the Use Case
We identify a useful assistant or agent opportunity, define the business outcome, and decide what should remain read-only versus what may take action.
02
Connect the Data
We connect approved data sources, APIs, MCP tools, and model providers such as Claude, OpenAI, or Gemini with a clear map of what the system can access.
03
Set Boundaries
We define permissions, allowed actions, human approval steps, guardrails, and the records or tools the assistant or agent must not touch.
04
Build & Test
We test factual quality, retrieval, normal workflows, unsafe requests, missing data, permissions, failure cases, duplicate actions, and API errors before launch.
05
Launch & Monitor
We deploy the workflow, add logs and monitoring, help your team get started, and remain available as the model, data, and business process evolve.
TECHNICAL TRUST
AI Security & Hosting
AI assistants and agents need the same engineering discipline as any other business system, with additional attention to data access, model providers, and agent actions.
- Use least-privilege access so each assistant or agent can reach only the data and tools it needs.
- Review model-provider data-retention and handling considerations before choosing Claude, OpenAI, Gemini, or another provider.
- Treat prompts, documents, and retrieved records as untrusted input and test for prompt injection and unsafe instructions.
- Require human approval for consequential actions and keep a clear boundary between read-only assistants and action-taking agents.
- Maintain logs and monitoring so the team can see what the workflow retrieved, drafted, or attempted to do.
Hosting can be cloud, on-premises, or hybrid. Existing work includes Cloudflare Tunnel for secure on-site access, Docker-based on-premises deployment, and Cloudflare OpenNext and R2 for a headless website.
Frequently Asked Questions
What is the difference between an AI assistant and an AI agent?
An assistant answers questions or helps with a defined task. An agent can take approved actions, such as monitoring data, flagging accounts, drafting replies, or routing requests. We define those boundaries before development begins.
Can you connect Claude, OpenAI, or Gemini to our systems?
Yes, where the provider and the available data access fit the use case. We help choose a model provider based on the workflow, data handling requirements, quality needs, and operational constraints rather than adding a model for its own sake.
Can you work with an existing database or API?
Yes, where access and technical constraints allow it. An existing project connected a mobile field sales application to a live MSSQL system, and the spare parts assistant connected business data through a custom MCP server.
What is MCP and why would we use it?
MCP is a way to connect an AI model to approved tools and data sources. It can provide a structured boundary around what an assistant is allowed to read or what an agent is allowed to do.
How do you protect private business data?
We use scoped access, server-side credentials, validation, explicit data boundaries, provider review, prompt-injection testing, human approval for important actions, and logs for the workflow. The exact controls depend on the systems involved.
How much does AI automation cost?
An AI Assistant (Starter) starts at $650, a full connected assistant starts at $2,800, an AI Agent starts at $4,500, and a broader platform typically starts at $12,000. API integration packages start at $400. These are starting prices, not final quotes.
What if we are not sure whether the project is an integration or an AI agent?
That is common. We can start hourly at $40 to $50 an hour while we understand the systems and the workflow, then usually move to a fixed price once the shape of the problem is clear.
PROOF FROM THE WORK
Related AI & Integration Work
The work below shows how AI assistants, MCP, existing databases, and connected applications can solve specific business problems.
Ready to build an AI-native workflow?
Tell us what your team needs to ask, automate, or connect. We will help you decide whether the right fit is an assistant, an agent, an API integration, or a focused combination of all three.
Start a project