Automate Inbound Client Calls with a Custom AI Agent
AI agents handle inbound calls using a speech-to-text service to transcribe the conversation in real time. A large language model then determines the caller's intent and uses APIs to take action in your CRM.
Key Takeaways
- AI agents use speech-to-text and a large language model to understand a caller's request and query business systems via API to respond.
- For professional services, an AI agent can answer new client questions about onboarding status by checking HubSpot and parsed SOW data.
- Syntora builds custom voice agents using Claude API and FastAPI that integrate directly with your existing CRM and project tools.
- A typical AI agent can handle an entire client status inquiry in under 45 seconds, completely freeing up your team.
Syntora architects AI voice agents for professional services firms to automate new client inquiries. The system uses Claude API to understand caller intent and a FastAPI backend to query HubSpot, reducing manual status checks by over 95%. This allows a firm to provide instant, 24/7 support for new clients without human intervention.
The complexity of an AI voice agent depends on the number of systems it must connect to. For a professional services firm, a system that checks new client onboarding status requires integrations with a phone provider like Twilio, your CRM like HubSpot, and a way to access SOW data. A project that also includes calendar scheduling would be a larger scope.
The Problem
Why Do Professional Services Firms Manually Handle Repetitive New-Client Calls?
Professional services firms often rely on a single project manager or coordinator to handle new client onboarding. When a client calls to ask, "What are the next steps?", that person has to stop their current task, open HubSpot, find the client's deal, check their email for the signed SOW, and then provide a manual update. Each call takes 5 to 10 minutes and breaks the concentration needed for high-value project work.
Standard business phone systems like RingCentral can route calls, but they cannot answer questions. Interactive Voice Response (IVR) systems are too rigid for natural conversation, forcing clients into a frustrating phone tree. While you can connect HubSpot to a basic website chatbot, that bot has no access to the specific context of a signed SOW or the real-time status of a multi-step onboarding workflow. The bot can't answer a specific question because it lacks the data and the logic.
The structural issue is that the phone system, the CRM, and the document storage are all separate data silos. They lack a central orchestration layer that can understand a natural language request from a phone call, parse a PDF document to find the relevant project details, and query a CRM API to get the current status. Off-the-shelf tools provide the pieces, but they don't provide the intelligent engine to connect them for your specific business process.
Our Approach
How Syntora Architects an AI Voice Agent for Client Onboarding
Our process would begin with a discovery phase to map your current client onboarding workflow. We would identify the 3-5 most common questions new clients ask over the phone and audit the systems where the answers live, typically HubSpot, your proposal software, and your project management tool. This audit defines the exact API endpoints the AI agent will need to access.
The technical architecture would use Twilio to manage the phone call and provide real-time speech-to-text transcription. A central FastAPI application, deployed on AWS Lambda for efficiency, would receive the transcript. We use the Claude API to perform intent recognition and entity extraction, identifying who is calling and what they need. The FastAPI service then makes authenticated API calls to HubSpot and a Supabase database (containing parsed SOW data) to fetch the client's onboarding status. The same Claude API then generates a natural, conversational response. This entire process typically has a response latency under 2 seconds.
Syntora would deliver a dedicated phone number for your AI agent. The agent can handle up to 10 concurrent calls and its performance is monitored for accuracy. You receive the complete Python source code for the FastAPI application, a runbook explaining how to manage the system, and a simple dashboard to review call logs. The monthly operating cost for cloud services is usually under $50 for a firm handling dozens of new clients per month.
| Manual Call Handling by a Project Manager | Automated Handling by a Syntora AI Agent |
|---|---|
| 5-10 minutes per call, interrupting other work | Under 45 seconds per call, runs 24/7 |
| Inconsistent information based on memory or quick checks | Consistent, real-time data from CRM and SOWs |
| Client waits for a callback if PM is busy | Instant answers with zero wait time |
| High labor cost tied to every client interaction | Operating cost under $50/month for typical volume |
Why It Matters
Key Benefits
One Engineer, From Call to Code
The person on the discovery call is the engineer who builds your AI agent. There are no handoffs to project managers or junior developers. You have a direct line to the expert building your system.
You Own All the Code
You receive the full Python source code and deployment configurations in your own GitHub repository. There is no vendor lock-in. The system is yours to modify or hand off to an internal team in the future.
A Realistic 4-Week Build
For a standard agent connecting to a CRM and one other system, the build, testing, and deployment takes about four weeks from kickoff. The initial discovery call provides a firm timeline and fixed price.
Simple Post-Launch Support
After an initial 8-week monitoring period, Syntora offers an optional flat-rate monthly support plan. This plan covers monitoring, bug fixes, and minor updates to the agent's logic, ensuring predictable costs.
Designed for Service Firms
We understand the context of SOWs, client onboarding, and project management. The AI agent is not a generic customer support bot; it's designed to handle the specific inquiries of new clients at a professional services firm.
How We Deliver
The Process
Discovery & Workflow Mapping
In a 30-minute call, we'll map your current client onboarding process and identify the most frequent inbound call types. You will receive a scope document within 48 hours detailing the proposed agent, technical architecture, and a fixed price.
Architecture & Access
Once you approve the scope, you provide read-only API access to the necessary systems like your CRM. Syntora finalizes the technical architecture for the voice agent and data flow, which you review before the build begins.
Build & Iteration
You get weekly updates with demos of the working AI agent. This allows for feedback on the agent's tone, conversational flow, and response accuracy. You'll be able to test the agent with real-world scenarios before it goes live.
Handoff & Support
You receive the full source code, a deployment runbook, and documentation. Syntora monitors the live agent for 8 weeks to ensure smooth operation. Afterward, an optional flat-rate monthly support plan is available.
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The Syntora Advantage
Not all AI partners are built the same.
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Assessment phase is often skipped or abbreviated
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We assess your business before we build anything
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Typically built on shared, third-party platforms
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Fully private systems. Your data never leaves your environment
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May require new software purchases or migrations
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Zero disruption to your existing tools and workflows
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Training and ongoing support are usually extra
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Full training included. Your team hits the ground running from day one
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Code and data often stay on the vendor's platform
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You own everything we build. The systems, the data, all of it. No lock-in
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