AI systems integration connects AI models and agents to the applications that hold your data, such as CRM, ERP, help desk and the data warehouse.
Salesforce Select Partner · Integration architects · 20+ enterprise implementations
Connecting AI to your systems, so it works with the records your teams already use.
We connect AI models and agents to your CRM, ERP, help desk and data warehouse through APIs, MCP servers and event triggers, with identity, data filtering and logging designed in from the first connection.
See the systems
- 15+Years of team experience
- 20+Enterprise implementations
- 60 minFree AI systems integration review, with a written plan
- 5.0/5Client satisfaction (CSAT)
Proven Success With
5.0/5 CSAT
New to AI systems integration?
What is AI systems integration?
It covers how AI is reached: through APIs, MCP servers, or event triggers that start AI work when a record changes.
It also decides what AI may see and do: the identity it acts as, the data it receives, and a log of every call.
Where you are starting from
Where does AI sit in your systems today?
For most teams, AI starts in a separate chat window. These are the three ways to bring it into the systems.
TodayAI in a separate chat window
- Inside your apps
AI where people work
AI answers and drafts appear inside the CRM, help desk or ERP screen.
Best when staff copy and paste between AI and your systems.
- On events
AI started by changes
A new case, order or document starts AI work without anyone asking.
Best for high-volume, repeatable work.
- As tools for agents
Systems exposed through MCP
Agents call scoped tools in your systems from any compliant platform.
Best when several agents need the same actions.
What we do
What does AI systems integration include?
Three groups of work, set up together for every connection.
your-ai-connections/
connect/
APIs
Model and system APIs with retries and limits.
MCP servers
Your systems exposed as scoped tools.
Event triggers
AI started by record changes and webhooks.
secure/
Identity
AI acts as the user or a named service account.
Data filtering
Only needed fields reach the model.
Secrets
Keys held in a vault, never in code.
operate/
Logging
Every prompt, tool call and result recorded.
Monitoring
Failures, latency and spend alerted.
Runbooks
What to do when a system or model is down.
Systems
Which systems can AI connect to?
The systems we connect most often. Others with an API or event feed follow the same pattern.
- 01
Salesforce
Cases, accounts and opportunities read and updated, with Salesforce permissions applied.
- 02
Microsoft Dynamics 365
CRM and finance records through its APIs.
- 03
SAP
Orders, materials and invoices through SAP APIs.
- 04
Oracle NetSuite
Customers, orders and invoices through NetSuite web services.
- 05
ServiceNow
Incidents and requests summarized, routed and updated.
- 06
Zendesk
Tickets triaged and replies drafted from your help center.
- 07
Snowflake
Governed warehouse data queried for answers and reports.
- 08
Databricks
Lakehouse tables feeding retrieval and analysis.
Architecture
How do you connect AI to CRM, ERP and help desk at once?
Each system is connected once, through shared layers that every AI use case reuses.
- CRM
- ERP
- Help desk
- Data warehouse
AI models and agents
- Identity and single sign-on
- APIs and MCP servers
- Events and webhooks
- Data filtering
- Logging and audit
One integration layer
A system connected for one use case is ready for the next.
Read first, then write
Write access is added after read-only use has been proven.
Model-independent
The layer works whichever model or agent platform calls it.
Identity, data access and logging
How do you control what AI can see and do?
Every connection gets a record like this one. Each rule protects one part of it.
AI connectionHelp desk to CRM
- Trigger
- New ticket created
- Acts as
- Signed-in agentor a named service account
- Data passed
- Accountopen casesentitlements
- Write access
- Draft only, approval to send
- Status
- PlanPhase inActivePhase outEnd of life
- Test coverage
Named trigger
Every connection starts from a defined event or request.
Nothing runs that nobody can explain.
Known identity
AI acts as the user or a named service account, and every call is logged against it.
Permissions apply and the audit trail means something.
Minimum data
Only the fields the use case needs are passed, with sensitive fields masked.
Less private data reaches the model.
Approval on writes
Changes that commit are drafted and approved by a person.
A person stays accountable.
Owned lifecycle
Each connection has an owner, a status and a review date.
Unused connections get switched off.
Tested connection
Contract tests run on every change to either side.
A system update cannot quietly break the AI that depends on it.
How it runs
How does an AI systems integration project run?
Four phases, read access before write access. Your written proposal sets the dates.
- Phase 1
Map
Know what AI needs to touch.
- Use cases and systems listed
- Data and permissions mapped
- Read and write actions agreed
- Phase 2
Connect
Read access first.
- APIs and MCP servers built
- Identity and data filters
- Logging on
- Phase 3
Act
Write actions added safely.
- Event triggers
- Approval on writes
- Contract tests
- Phase 4
Run
Kept working as systems change.
- Monitoring and alerts
- Runbooks
- Reviews and tuning
Cost and timing
What it costs and how long it takes
The review is free
A 60-minute architecture review of your AI integration setup, with a written plan you keep.
A fixed-scope proposal first
Before any work starts you get a written proposal: a fixed-scope project with milestones, or a monthly plan. You approve it, or you do not.
Timing follows scope
How long it takes depends on what is in scope. The proposal states the milestones, so you see the timeline before you commit.
Client stories
Client work we have delivered
Real engagements, described by industry. Each story covers the starting position, what we built and how we delivered it, end to end.
Commercial & Business ServicesOne Operating Backbone From Quote to Invoice for a Fire Protection ContractorSales Cloud, work orders and scheduling for a fire protection contractor, synced two-way with QuickBooks Time, Dashpivot and Xero through custom Apex REST.Sales Cloud · Field Service · Salesforce Platform · Apex RESTRead the story 
Financial ServicesSelf-Hosted AI Research Infrastructure Behind a Salesforce Deal EngineSelf-hosted AI agent infrastructure for a US private equity advisory firm: n8n workflows, PostgreSQL, web research and Google Drive mandate documents, deployed with Coolify and writing results back to Salesforce.n8n · PostgreSQL · Coolify · FirecrawlRead the story 
EducationOne Tutoring Calendar Across Salesforce and TeachWorksSalesforce development for an Australian tutoring provider: a custom session calendar, two-way TeachWorks appointment sync, attendance and completion mapping, and session notes into after-session reports.Salesforce Platform · Lightning Web Components · Apex · TeachWorks APIRead the story Client reviews
What clients say about working with our architects
See how teams describe working with SynconAI, from first scope to production delivery.
Salesforce Select Partner30+ Salesforce certificationsDelivery from Delaware & Sydney, worldwide
Simply Outstanding
“SynconAI Consulting are Simply the Best in the Business When it comes to Salesforce implementation and AI-powered solutions, SynconAI are in a league of their own. Their expertise, dedication, and ability to deliver results that truly move the needle sets them apart from every other consulting partner we've worked with. What they achieved with our Sales Cloud, Service Cloud, and custom Agentforce agent has completely transformed how we operate streamlining our pipelines and our customer service, and automating tasks that used to consume hours of our team's time. They don't just implement technology they transform businesses. If you want the best, you work with their team.”
Sales CloudService CloudAgentforce
Jack BennettConsumer Goods & Retail · United States
“I had a very urgent deadline for our project reporting to be delivered and needed to build the module, dashboard and output reports in Salesforce. SynconAI were very responsive - they met with me online, responded to my emails quickly and took calls - whatever was needed to progress the work quickly. We are thrilled with the outcome and will continue to work with SynconAI in the future to continue to build our Salesforce capability and platform.”
Sales CloudService CloudNonprofit Cloud
Salesforce Managed ServicesAustraliaSalesforce Verified
“The team at SynconAI were fantastic, and promptly delivered on each project. They were able to guide us through every stage and made sure we were satisfied with the outcomes on multiple scopes of work.”
Sales CloudSlackFlowAgentforceMuleSoft
ManufacturingAustraliaSalesforce Verified
“They have been great and helping us transform out business by bringing what I conceptualize to life. Great at translating process/workflow needs into a solution. Been a pleasure work with and they're a critical part of our team and will be instrumental into bringing about my vision.”
Sales CloudFinancial Services CloudArchitectureAI
Financial ServicesUnited StatesSalesforce Verified
“Working with SynconAI was a seamless and highly professional experience from start to finish. They took the time to deeply understand our business processes before designing and implementing a Salesforce solution tailored specifically to our operational needs. The team demonstrated strong technical expertise across Salesforce configuration, automation, integrations, reporting, and user experience design.”
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Frequently asked questions
Connecting AI to your systems, answered.
Straight answers about APIs, MCP, events, data access, logging and middleware.
Connecting AI models and agents to business systems such as CRM, ERP, help desk and the data warehouse, through APIs, MCP and events, with identity, data filtering and logging.
Through Salesforce APIs, Agentforce actions or MCP, with the Salesforce permissions of the signed-in user or a named integration user applied.
An API is how a system exposes data and actions. MCP is an open standard that packages actions as tools an AI agent can find and call, usually built on those APIs.
Yes. Event triggers, such as a new ticket or order, can start AI work. Steps that commit money, data or a customer promise still wait for approval.
AI acts as the user or a scoped service account, only the fields a use case needs are passed, and sensitive fields can be masked before any model sees them.
The trigger, the identity, the data passed, the model response, every tool call and the final result, kept where your security team can search it.
Yes. Snowflake, Databricks, BigQuery and others, through governed views, so AI answers from the same numbers as your reports.
Yes. AI can call your existing MuleSoft, Boomi or other integration flows, which keeps one place for system connections.
Salesforce, Agentforce and MuleSoft are trademarks of Salesforce, Inc. Microsoft Dynamics 365 is a trademark of Microsoft. SAP is a trademark of SAP SE. Oracle NetSuite is a trademark of Oracle. ServiceNow is a trademark of ServiceNow, Inc. Zendesk is a trademark of Zendesk, Inc. Snowflake is a trademark of Snowflake Inc. Databricks is a trademark of Databricks, Inc. BigQuery is a trademark of Google LLC. Boomi is a trademark of Boomi, LP. SynconAI is an independent consulting firm; apart from its Salesforce partner status, it is not affiliated with or endorsed by these companies.
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