AI Integration

We add intelligence to the systems you already run

We do not ask you to throw away your ERP, CRM, helpdesk or document store. We connect AI models to your real workflows — inside SAP, Salesforce, Dynamics, Zendesk, SharePoint, mobile and web — so day-to-day work gets faster, more accurate and measurable.

6-10 wks

From kick-off to the first AI use case live inside one of your business systems

-40%

Average time saved on repetitive back-office and customer support tasks

0

Forced migrations required: AI slips into what already works

Integrate, don’t replace

Every company carries years of rules, integrations and data inside its systems. Re-platforming just to add AI is expensive, risky and slows people down. We do the opposite: we plug language models, agents and machine learning into the tools your teams already use. People notice the change — they don’t suffer it.

We pick the high-value spots with you

Before writing code we identify 3-5 points in your workflow where AI creates measurable value: shorter queues, faster quotes, fewer errors, more revenue.

Integrated into the interface

AI does not become yet another portal: it shows up as a button, suggestion, summary or copilot inside the tool people already open every morning.

Humans stay in control

For sensitive actions we design human-in-the-loop: AI proposes, a person approves. Every decision is tracked, auditable and reversible.

Live snippet

A webhook that brings AI replies into Zendesk

Example: when a new ticket arrives we classify it, search the internal knowledge base and suggest a draft reply to the human agent.

python@lbd studio/ai.snippet

                

Where we typically plug in

Mapping your stack is the first move: every system has its own APIs, limits and users. These are the most frequent integration points.

ERP & Finance

SAP, Oracle, Dynamics, Zucchetti

We automate invoice reconciliation, anomaly detection, expense classification and report generation directly inside standard screens.

  • Invoice and delivery-note reading with vision models
  • Automated alerts on budget deviations
  • Cash flow and due-date forecasting
CRM & Sales

Salesforce, HubSpot, Dynamics 365

We give sales a copilot that summarises conversations, suggests next best actions, drafts proposals and keeps CRM fields up to date for them.

  • Call and email summaries with data extraction
  • Proposal generation from templates
  • AI-powered lead scoring and prioritisation
Helpdesk & Support

Zendesk, Freshdesk, ServiceNow

We triage tickets with AI, suggest replies, auto-answer where possible and route only complex cases to human agents.

  • Automatic triage by area, urgency and product
  • Knowledge base kept current via RAG
  • Inline reply suggestions
Document & Knowledge

SharePoint, Google Drive, Confluence, Notion

We make all corporate documents — policies, manuals, contracts, specs, internal wikis — searchable in natural language.

  • Semantic search with source citations
  • On-demand summaries and version diffs
  • Access controls mirrored from the originals
Internal communication

Microsoft 365, Google Workspace, Slack, Teams

We bring copilots into emails, documents and chats: people never change tool, they just get new intelligent shortcuts.

  • Conversational bots with secure data access
  • Automatic thread and call summaries
  • Guided writing matching your corporate tone
Your own products

Your web and mobile apps

We add smart search, contextual suggestions and AI automations to the products you already sell — without rewriting them.

  • Optional per-tenant AI features
  • Metering and billing for token usage
  • Safe fallbacks when the model is unsure

How we move, step by step

A simple method designed to deliver tangible outcomes by month two.

01

1. Systems and workflow audit

Two weeks with your IT, operations and business leads to understand what you use, who uses it, where the bottlenecks are and where AI is truly worthwhile.

Output: system map, 5-10 use cases scored by impact and feasibility, recommendation.

02

2. Pilot on a single use case

Together we pick the first use case — the best balance of impact and risk — and take it to controlled production with a small user group.

Output: AI integration live inside the existing system, adoption metrics, structured feedback.

03

3. Rollout, observability and scale

We extend to other departments and stack new use cases next to the first. We build dashboards for cost, quality and errors. The AI platform grows without losing control.

Output: internal AI platform, access policies, runbook for new use cases, continuous support.

What we integrate with

We speak standard protocols (REST APIs, webhooks, native connectors, events) to enter your systems without friction.

ERP & Business

SAP S/4HANA, Oracle Fusion, Dynamics 365, Zucchetti, Odoo, NetSuite

CRM & Sales

Salesforce, HubSpot, Pipedrive, Zoho, Dynamics Sales

Support

Zendesk, Freshdesk, Intercom, ServiceNow, Jira Service Management

Collaboration

Microsoft 365, Google Workspace, Slack, Teams, Confluence, Notion

Data

Snowflake, BigQuery, Databricks, Postgres, SQL Server, Oracle DB

AI models

Claude (Anthropic), GPT (OpenAI), Azure OpenAI, AWS Bedrock, Mistral, Llama, custom models

Let us start with the map of your systems

One 45-minute call: you tell us what you run, we tell you where AI can deliver real results before the quarter ends.

Frequently asked questions

Questions about AI integration into existing systems

How we bring AI inside your tools without forcing migrations or rewrites.

Do we need to replace our ERP or CRM to integrate AI?
No. We work with SAP, Oracle, Dynamics, Salesforce, HubSpot, Zucchetti and other common systems through APIs, native connectors, events and webhooks. AI adds capabilities inside existing screens without touching the architecture.
Do users need to learn a new tool?
Rarely. AI appears as a button, inline suggestion, automatic summary or copilot inside the tool they already use. Training is minimal: typical adoption in pilot departments exceeds 70% within the first month.
How much does AI token / API usage cost?
It depends on volume, but every integration ships with metering, caching and fallbacks. During the first two months we monitor cost per request and per user, then optimise model and prompts: we typically cut costs by 40-60% versus the first version.
What if tomorrow we want to switch AI providers?
We build an abstraction layer: your code talks to an interface, not directly to Claude or GPT. Switching models is a configuration change, not an architectural one. We avoid vendor lock-in.
Can AI be integrated on-premise?
Yes. For sensitive data we use self-hosted open source models (Llama, Mistral, Qwen) on dedicated GPUs inside your datacentre or private cloud, with the same APIs as a cloud model. Performance today is close to frontier models for most enterprise use cases.