An AI agent is a model given instructions, tools and data access, so it can carry out steps of a task as well as answer questions.
Two Agentforce agents live · Salesforce and OpenAI Select Partner · Human approval built in
AI agents on any platform, built to act safely in the systems you already run.
We design, build and test AI agents on Salesforce Agentforce, Claude, OpenAI, n8n and Microsoft Copilot Studio, with narrow tools, MCP servers, approval steps and logs.
Pick a platform
- 15+Years of team experience
- 20+Enterprise implementations
- 60 minFree AI agents review, with a written plan
- 5.0/5Client satisfaction (CSAT)
Proven Success With
5.0/5 CSAT
New to an AI agent?
What is an AI agent?
Its tools are narrow actions in your systems, such as looking up an order or drafting a refund, often exposed through the Model Context Protocol (MCP).
A person approves any step that commits money, data or a customer promise, and every action is logged.
Where you are starting from
Which platform should your AI agent run on?
We build on all of them. The right one depends on where the work and the people already are.
Where does the work live?
- Path 01In Salesforce
Salesforce Agentforce
Cases, opportunities and customer records are in Salesforce, and users work there.
- Agentforce Builder and Salesforce actions
- Grounded in Salesforce and Data 360 data
- See our Agentforce consulting page
- Path 02Across many apps
Claude or OpenAI, with n8n or code
The job crosses email, ERP, help desk and chat.
- Model API with tool use
- n8n or code for orchestration
- Self-hosting possible
- Path 03In Microsoft 365
Microsoft Copilot Studio
Staff work in Teams, Outlook and SharePoint.
- Agents published to Teams and Microsoft 365 Copilot
- Power Platform connectors
- MCP servers as tools
One platform per agent, chosen on facts, with tools that can be shared through MCP
What we do
What does AI agent development include?
Six pieces of work, the same on every platform.
01Platform choiceAgentforce, Claude, OpenAI, n8n or Copilot Studio, picked by where the work lives.
- Where the data and users are
- Licenses you already hold
- Hosting and data rules
02Agent designInstructions, scope, tools and the points where a person decides.
- One job, clearly bounded
- What the agent must never do
- Handoff to a person
03Tool and MCP server designNarrow, safe actions in your systems.
- Read tools before write tools
- Inputs validated
- MCP servers with scoped access
04Human approvalApprovals in Slack, Teams, email or Salesforce.
- Limits per action
- A named approver
- Every decision logged
05Testing and evaluationReal cases replayed and graded before release.
- Task completion
- Tool choice
- Refusals and handoffs
06Deployment and monitoringLive with logs, alerts and a named owner.
- Every tool call logged
- Alerts on failures
- Regular transcript reviews
Autonomy
How much should an AI agent do on its own?
Each action is placed on a tier. The tier decides whether a person approves it.
- Never
ExamplesDeleting records, changing permissions, paying out money.
ControlsNo tool exists for it, so the agent cannot attempt it.
- Approve first
ExamplesRefunds, contract changes, emails to customers.
ControlsThe agent drafts; a named person approves before it runs.
- Act and report
ExamplesUpdating a case status, booking a slot, creating a task.
ControlsRuns alone within limits, logged and reviewed.
- Read freely
ExamplesLooking up orders, policies and account history.
ControlsRead-only tools scoped to what the user may see.
Tools and MCP
What tools does an AI agent need, and where does MCP fit?
Each tool is one narrow action in one or more systems. MCP servers expose them so any compliant agent can use the same set.
Agent tools
- Look up order
- Check refund policy
- Draft refund
- Create case
- Book technician
Your systems
- ERP
- Knowledge base
- CRM
- Field service
One action per tool
Small tools are easier to test, approve and log than one broad one.
Scoped access
Each MCP server holds only the permissions its tools need.
Shared across platforms
Claude, OpenAI and Copilot Studio agents can call MCP servers, so one tool set serves several agents.
Testing
How do you test an AI agent before release?
Real cases, replayed on every change. An agent ships when it meets the rules agreed with you.
Task completion
HowReal cases replayed end to end
Release ruleAgreed pass rate met
Tool choice
HowEach tool call checked against the expected one
Release ruleNo wrong write actions
Approval steps
HowCases that must stop for a person
Release ruleEvery one stops
Refusals
HowRequests outside scope or permissions
Release ruleRefused and handed to a person
Prompt injection
HowInstructions hidden in emails and documents
Release ruleIgnored, flagged and logged
Regression
HowThe full set after any change
Release ruleNo new failures
How it runs
How does an AI agent project run?
Five stages from one job to a live agent. Your written proposal sets the scope and dates.
- 01
Choose
One job with a clear payoff.
- Use case and owner
- Platform chosen
- Success criteria
- 02
Design
Scope, tools and approvals.
- Instructions and limits
- Tool list
- Autonomy tiers
- 03
Build
Agent, tools and MCP servers.
- Tools and MCP servers
- Approval steps
- Logging
- 04
Test
Real cases graded.
- Test set
- Injection checks
- Fixes
- 05
Run
Live with an owner.
- Pilot group
- Monitoring and alerts
- Transcript reviews
Cost and timing
What it costs and how long it takes
The review is free
A 60-minute architecture review of your AI agent 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.
Communications, Media & TechnologyFour Production AI Systems for a Japanese Contact Centre OperatorCustom AI for a Japanese contact centre operator: recorded and live Japanese call transcription, 16-field emergency form extraction with human review, a bilingual knowledge base, and realtime operator assistance.Custom AI · Speech-to-text · Large language models · Vector searchRead the story 
Financial ServicesAI Deal Matching That Screens Companies Against Every Investor MandateSales Cloud, Agentforce, Data 360 and Prompt Builder for a US private equity advisory firm: mandates, AI first-pass ranking, deep scoring with rationale, and deals created from approved matches.Sales Cloud · Agentforce · Data 360 · Prompt BuilderRead 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 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.”
SalesforceExperience CloudCustom DevelopmentAutomationReporting
Salesforce ImplementationSalesforce Verified
Frequently asked questions
AI agents, answered.
Straight answers about platforms, MCP, human approval, testing and live agents.
The design, build and testing of AI agents that take actions in business systems, with narrow tools, human approval on steps that commit, logging, and a test set run before every release.
A chatbot answers. An agent can also act: it calls tools to look up records, draft changes or update systems, within limits you set and with approval where needed.
Salesforce Agentforce, Anthropic Claude, OpenAI, n8n and Microsoft Copilot Studio. We choose by where the work and the users are.
The Model Context Protocol is an open standard for connecting AI agents to tools and data. Anthropic introduced it, and it is now hosted by the Agentic AI Foundation under the Linux Foundation.
Every action gets an autonomy tier. Anything that commits money, data or a customer promise waits for a named approver, and every decision is logged.
Yes. Two of our Agentforce agents run on a real Salesforce org, and you can see them in our AI agents library.
If the work lives in Salesforce, Agentforce is usually the better fit. If it crosses many tools, Claude or OpenAI with n8n often is. Our Claude and n8n page covers that option.
Tools are narrow and scoped, write actions need approval, text from emails and documents is treated as data, and injection cases are part of the test set.
Salesforce, Agentforce, Data 360 and Slack are trademarks of Salesforce, Inc. Claude and Anthropic are trademarks of Anthropic, PBC. OpenAI is a trademark of OpenAI. n8n is a trademark of n8n GmbH. Microsoft Copilot Studio, Microsoft 365, Teams, Outlook, SharePoint and Power Platform are trademarks of Microsoft. Linux Foundation is a trademark of The Linux Foundation. SynconAI is an independent consulting firm; apart from its Salesforce and OpenAI partner status, it is not affiliated with or endorsed by these companies.
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