We connect Claude and GPT to your CRM, helpdesk, ERP, data warehouse, and internal systems — usually via MCP. No rip-and-replace. AI shows up where the work already happens.
Trusted by teams shipping production software
We’re an AI integration company that wires LLMs into your existing stack via MCP servers, direct API integrations, or hybrid patterns — same model, every tool, no data leaks. We built Arlo on this exact pattern: Claude connected to 100+ analytics platforms, pass-through architecture, zero data retention. The same shape works for your CRM, helpdesk, or ERP.
AI lives in a separate tab.
A chat window in the browser, disconnected from the systems where the real work lives. So it gets used for one-off questions and ignored for the actual workflows.
The data never reaches the model.
The leads sit in your CRM, the tickets in your helpdesk, the contracts in your data room. AI can't see any of it, so it can't answer anything specific to how you run.
Off-the-shelf connectors don't fit.
Your homegrown CRM, custom ERP, or internal admin tool doesn't have a tidy plug-in. The integration has to be built to match your systems, not the other way around.
The systems we connect AI to most often. The integration pattern adapts per tool, but the architecture stays consistent.
- 01
CRM integration
Salesforce, HubSpot, Pipedrive, Attio. Read leads, contacts, deals, and activities. Write back updates, notes, and follow-up tasks.
- 02
Helpdesk integration
Zendesk, Intercom, Help Scout, Freshdesk. Triage tickets, draft replies, surface related conversations, and escalate the hard ones.
- 03
ERP integration
NetSuite, SAP, and custom ERPs (we build a lot of those). Read inventory, orders, and financials. Write back with the right guardrails.
- 04
Data warehouse
BigQuery, Snowflake, Redshift, Postgres analytics. Natural-language querying with safe, validated SQL generation.
- 05
Analytics platforms
GA4, Search Console, Meta Ads, Google Ads, Mixpanel, Amplitude. Live querying via MCP — the exact Arlo pattern.
- 06
Project & collaboration
Linear, Jira, Notion, Slack, Microsoft 365. Wire AI into the daily work systems where decisions actually get made.
- 07
Email & calendar
Gmail, Outlook, Google Calendar. Drafting, summarization, and calendar negotiation without the copy-paste shuffle.
- 08
Internal & custom systems
Your internal admin tool, your homegrown CRM, your custom ERP. If it has an API, we can wire it in.
- 09
MCP server development
We write custom MCP servers — the bridge layer between your systems and any MCP-compatible model or agent.
Integrations break when the data flow and auth model get figured out mid-build. We lock those first.
Discover
1 week. Which systems, which workflows, where the value is. We map compliance constraints and how data needs to flow before anything gets wired.
Architect
1 week. MCP servers vs. direct API, the auth model, a data-flow diagram. Locked and documented before a line of integration code is written.
Build
2–4 weeks. MCP servers plus integration code plus a UI for testing, connected to your real systems through test credentials.
Pilot
1–2 weeks. Real users on real data. We watch the traces and tune the prompts, guardrails, and tool definitions.
Run
Ongoing. Deploy, monitoring, and maintenance. APIs change and tools evolve — we keep the integrations healthy.
We're protocol- and model-agnostic, but we have strong defaults. We pick based on the system, not the trend.
- MCPMCP (Model Context Protocol)Tool protocol
- REST / GraphQLDirect API
- WHWebhooksEvent triggers
- Claude (Anthropic)Reasoning model
- GPT (OpenAI)Reasoning model
- Open models via Bedrock / AzureHosted LLMs
- MCP SDKs (TS, Python)Tool SDK
- LangChainAgent framework
- Vercel AI SDKAgent framework
- Direct SDKsModel SDKs
- OAOAuth per-userAuth model
- SAService accountsAuth model
- KEYAPI keys (encrypted)Auth model
- SSOSSO via WorkOS / ClerkAuth model
- pgvectorVector store
- PostgresDatabase
- RDRedisCache
- S3 / R2Object storage
- AESAES-256-GCM tokensEncryption
- PTPass-through (no retention)Data minimization
- {}Audit logsCompliance
- S2SOC 2 readyCompliance
“Futur Labs shipped in six weeks what our internal team couldn't in eighteen months.”
Focused Integration
One system wired into AI — CRM, helpdesk, or analytics. An MCP server plus a UI to test and use it.
- 1 MCP server / system
- Auth + security setup
- Test + production deploy
- 3–5 weeks to ship
Arlo
Our own product. Claude wired into 100+ analytics platforms via MCP, queried in natural language. Pass-through architecture with AES-256-GCM token encryption and zero data retention — the privacy pattern we replicate for client stacks.
Agency ERP
AI wired directly into our own ERP for client triage, scope review, and project status. The same architecture and guardrails we ship when integrating AI into client systems.
It's connecting an LLM (Claude, GPT, etc.) to your existing systems so it can read and write the data those systems hold. Most usefully via MCP (Model Context Protocol) — the open standard for connecting models to tools. We build MCP servers, wire up direct API integrations, or use existing connectors depending on the system.
Both terms apply. We integrate AI capabilities into existing systems, and we integrate multiple systems together using AI as the glue. Most engagements involve a mix.
Example: a sales team uses Salesforce, Gmail, and Slack. We wire Claude into all three via MCP. Reps ask 'who's the highest-priority lead this week and why' — Claude pulls from Salesforce, reads recent email threads, surfaces the answer. Or: 'draft a follow-up to Acme based on our last 3 calls.' The integration is where the value is.
Model Context Protocol is the emerging standard for connecting LLMs to tools (Anthropic, OpenAI, and others are adopting it). Building on MCP means your integrations work across model providers and across different agent frameworks. It's the format-once-use-everywhere pattern for AI tool access.
Yes. If it has an API or a webhook, we can wire AI into it. We've done Salesforce, HubSpot, Zendesk, Intercom, Notion, Linear, Jira, GitHub, Stripe, QuickBooks, internal databases, and a long tail of custom systems. The pattern is the same — we just adapt to your tool's specifics.
We design integrations with data-minimization patterns: pass-through queries (no data storage), per-user OAuth (no shared credentials), encrypted token storage, audit logs of every model call. Arlo, one of our own products, uses exactly this pattern — pass-through, AES-256-GCM token encryption, zero data retention. We can replicate it for you.
A few questions about the project so we come prepared — then we'll set up a short call to dig in.