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Your AI Can't See Your Data. That's Why It Can't Do Your Job.

If you're a founder who's tried to build an AI workflow and hit the wall at 'how does it access Salesforce,' you've found the missing piece.

You use ChatGPT for drafting emails and brainstorming. But what if AI could read your CRM, check your inventory, book appointments, process insurance claims, and answer customers -- automatically? We connect Claude and ChatGPT to your existing business systems so AI stops being a chatbot and starts being an employee. Not a science project. Not a 6-month R&D initiative. A working AI integration in 2 to 4 weeks that plugs into the tools you already use.

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AI System Integration

AI integration connects large language models like Claude and ChatGPT directly to your business systems via APIs, webhooks, and secure data pipelines. Instead of copy-pasting information into a chat window, the AI reads live records from your CRM, ERP, or e-commerce platform and takes action on your behalf. The result is an AI that knows your customers, your inventory, and your workflows without manual input.

What is holding your current website back?

Common gaps we find in nearly every audit.

Your AI tools are isolated from your real data, so every useful task still requires a human to pull a report, paste it in, and interpret the output.
Risk: Staff spend hours on data retrieval work that should be automated, and decisions get made on stale information because the loop is too slow.
You have tried Zapier automations or no-code connectors, but they break on edge cases, cannot handle conditional logic, and offer no visibility when something goes wrong.
Risk: Fragile automations erode trust in the system, and when they fail silently, customers fall through the cracks or inventory numbers go out of sync.
Your industry handles sensitive data under HIPAA, SOC 2, or PCI requirements, and every vendor demo sidesteps the question of how compliance actually works in practice.
Risk: Deploying an AI integration without a clear data handling architecture exposes you to audit findings, customer liability, and the cost of pulling the system apart later.

How We Build This Right

Every safeguard, built in from Day 1.

HIPAA-Ready Architecture

We configure data pipelines so protected health information is never stored in model context logs, third-party caches, or vendor training datasets. Business Associate Agreements are in place before a single record moves.

Scoped Access Controls

AI agents receive read or write permissions only for the specific objects and fields the workflow requires. No broad API keys, no admin-level credentials sitting in environment variables.

Audit Logging and Observability

Every action the AI takes against your systems is logged with a timestamp, the triggering input, and the system response. You have a full trail for internal review or external audit without digging through raw API logs.

What We Build

Purpose-built features for your industry.

Live CRM and ERP Read-Write

The AI queries and updates records in Salesforce, HubSpot, NetSuite, or your custom database in real time. It can pull a customer's order history mid-conversation, update a deal stage after a call, or flag an account for review without a human touching the keyboard.

Multi-System Action Chains

A single customer request can trigger a sequence across systems: verify identity in your auth layer, check inventory in Shopify, create a support ticket in Zendesk, and send a confirmation via your email platform. We design the decision logic so the AI handles exceptions correctly, not just the happy path.

Model-Agnostic Deployment

We build integrations that work with Claude, GPT-4o, or both, and we do not lock you to one provider. If your use case benefits from routing specific queries to a faster or cheaper model, the architecture supports that without a rebuild.

Monitoring, Alerts, and Iteration

After deployment we instrument the integration so you can see task completion rates, failure points, and latency. When a new API version breaks a connector or a workflow needs a new branch, we handle it under a retainer or a defined maintenance agreement.

Built on a Modern, Secure Stack

Claude APIOpenAISupabasepgvectorVercelElevenLabsTwilioStripeHubSpot APIShopify APISlack API

Our Development Process

From discovery to launch. Quality at every step.

01

Systems and Workflow Audit

1 week

We map the specific workflows you want to automate, identify every system involved, and document the data objects the AI will need to read or write. We also flag any compliance requirements before any code is written.

02

Integration Architecture and Credentials Setup

1-2 weeks

We design the API connection layer, configure scoped credentials and environment secrets, and establish logging infrastructure. For HIPAA or SOC 2 contexts, we confirm BAAs and data residency requirements are satisfied at this stage.

03

AI Agent Build and Workflow Logic

1-2 weeks

We write the prompt architecture, tool definitions, and conditional logic that govern how the AI interprets requests and takes action across your connected systems. Edge cases and failure states are defined explicitly, not left to the model to guess.

04

Testing, Handoff, and Go-Live

1 week

We run the integration against real data in a staging environment, walk your team through how to monitor and adjust it, and move to production. You receive documentation covering every connection, credential location, and escalation path.

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Frequently Asked Questions

Pricing is pretty straightforward once we know your scope. A simple AI chatbot connected to your website and FAQ database runs $8,000 to $15,000. Connecting AI to a single system -- your CRM or Shopify store -- is $15,000 to $40,000. Multi-system integration across 3 to 5 tools with workflow automation runs $40,000 to $100,000. Enterprise builds with custom RAG, multiple departments, and compliance requirements range from $100,000 to $250,000. All fixed-price after a 1-week discovery sprint. No hourly billing surprises.
Honestly, if it has an API or a database, we can connect AI to it. In production we've integrated Claude and ChatGPT with Shopify, Salesforce, HubSpot, Slack, SAP, Oracle, PostgreSQL, MongoDB, Epic, Cerner, FedEx, DHL, Stripe, Twilio, and dozens of others. Custom ERPs that nobody outside your industry has heard of? Usually fine. The question isn't really whether we can connect to your system -- it's what's worth connecting first.
ChatGPT out of the box knows nothing about your business. It doesn't know your customers, your inventory, your pricing, or your policies. Our integrations fix that by connecting AI directly to your actual data sources in real time. So instead of a nurse copying patient info into a chat window and hoping the AI gives useful output, she just says "schedule a follow-up with Dr. Patel" -- and the AI checks the Epic calendar, finds the Thursday slot, and books it. That's the difference.
Yes, and this is something we take seriously. All data stays in your infrastructure. We use the Claude API with enterprise-grade encryption -- not the consumer ChatGPT product. For healthcare clients we build HIPAA-compliant systems with BAAs signed and in place. For financial clients we follow FCA, SEC, and PCI DSS requirements. AI processes data in memory and doesn't store it between sessions. Your data doesn't leave your systems.
Timelines depend on scope, but here's a realistic breakdown: a simple AI chatbot is 2 to 3 weeks. Single-system integration -- connecting AI to your CRM, for example -- takes 3 to 4 weeks. Multi-system integration with workflow automation runs 6 to 10 weeks. Enterprise deployments with compliance requirements and team training take 10 to 16 weeks. And you see working demos every week throughout, not just at the end.
Both, and the distinction matters. We build AI agents that take real actions inside your systems -- booking appointments, updating CRM records, processing returns, sending emails, rerouting shipments, generating reports. Using MCP protocol and function calling, the AI doesn't just chat about what should happen. It actually executes the workflow. With human-in-the-loop controls for anything sensitive, so you're never flying completely blind.
We primarily use Claude API from Anthropic -- it's genuinely better for reasoning, instruction-following, and handling long context windows than most alternatives. For specific use cases we also bring in OpenAI's GPT-4o. Document processing and semantic search runs on pgvector embeddings. Voice integrations use ElevenLabs. We're not locked to one vendor, which matters -- because the right model for a healthcare scheduling system in Boston isn't necessarily the right model for an ecommerce returns workflow in Austin.
Yes, and it's a clean business model for agencies that want to offer AI without building an AI practice from scratch. You sell the AI features to your clients under your own brand. We build the integrations, connect the systems, and handle all the technical complexity on the back end. You sell and support the client relationship. Typical agency markup is 40 to 60 percent. We've built white-label AI solutions for agencies with 50 or more clients -- it scales well once the model is set up.
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