Build AI Tools to Automate Your Sales Pipeline
Custom AI automation qualifies leads by analyzing their fit against your ideal customer profile. It also summarizes sales calls and drafts personalized follow-up emails for your reps.
Syntora specializes in designing and building custom AI automation systems for sales pipeline improvement. By applying Claude API expertise in multi-step workflows and structured output parsing, Syntora helps businesses understand sales interactions and automate lead qualification and follow-up processes.
This involves designing and building a custom system that integrates with your existing CRM, email, and call recording software. Using the Claude API, we develop internal tools specifically tailored to understand your unique sales process and terminology. The goal is a system operating on your own infrastructure, ensuring data privacy and full ownership of the code. Syntora has extensive experience building production systems on Claude API for multi-step workflows, structured output parsing, and context window management, which are directly applicable to the complexities of sales process automation.
What Problem Does This Solve?
Most teams start with their CRM's built-in automation, like HubSpot Workflows. These tools are great for simple triggers, like sending a template when a deal stage changes. But they cannot understand conversational context. They cannot read a meeting transcript to generate a unique summary or identify a customer's primary objection.
A 10-person sales team might look at conversation intelligence platforms like Gong, but the per-seat pricing is designed for larger organizations. This leaves teams trying to stitch together multiple services. A common attempt is to use Zapier to connect a call recording folder in Google Drive to an AI transcription service, then to an AI model for summarization, and finally back to the CRM. This workflow fails for two reasons.
First, Zapier has processing limits and timeouts not designed for large files like 30-minute audio recordings. The workflow often breaks without a clear error message. Second, the per-task pricing becomes extremely expensive at scale. A single call can consume 4-5 tasks. For a team handling 200 calls a week, this translates to nearly 1,000 tasks, pushing a Zapier bill into hundreds of dollars monthly for just one automated process.
How Would Syntora Approach This?
Syntora would start by engaging with your team for discovery, identifying key integrations and process requirements. We would connect to your source systems using their native APIs, for example, the HubSpot API for deal data, an AWS S3 event trigger for new call recordings, and the Google Calendar API for meeting context. This process allows us to establish a clear picture of your sales interactions and analyze existing call data to understand your unique sales language and patterns.
The core of the system would be an event-driven pipeline built on AWS Lambda. When a new MP3 file indicating a call recording lands in S3, a Python function would trigger. This function would send the audio to a transcription service like AssemblyAI, which typically returns a timestamped transcript quickly. The resulting text would then be fed to the Claude API with a custom prompt engineered to extract specific elements like action items, customer objections, and budget discussions. Our work on AI product matching and document processing pipelines has given us significant experience in achieving precise structured output parsing from complex text.
The structured JSON output from Claude would then be passed to a FastAPI service. This service could update the corresponding deal record in HubSpot with a concise summary and action items, and also call the Gmail API to create a personalized follow-up email draft for the sales rep. Pydantic would be used to ensure all data moving between services is correctly formatted, a pattern we apply across our production systems.
Deployment of such a system would typically be on your AWS account, using the AWS CDK for infrastructure-as-code. Syntora can also design and build a simple dashboard, potentially using Streamlit, to provide call analytics and insights. Access management would be implemented, for example, through Supabase with role-based permissions, to ensure secure operation.
What Are the Key Benefits?
Go Live in 4 Weeks, Not 4 Quarters
A focused 4-week build gets a production system into your reps' hands. No lengthy enterprise rollouts or extended training cycles.
Pay Once and Own the System
This is a single project cost, not a recurring per-seat SaaS fee that punishes you for growing your team. You own it forever.
The Code Lives in Your GitHub Repo
You get the complete Python source code and deployment scripts. You are not locked into a proprietary platform and can have any developer maintain it.
Alerts When an API Fails
We use structlog for structured logging and route critical errors to a Slack channel. You know instantly if an API key is invalid or a summary fails.
Works Inside Your Existing CRM
Integrates directly with HubSpot, Salesforce, and Pipedrive. The AI works inside the tools your team already uses daily.
What Does the Process Look Like?
System Audit (Week 1)
You provide read-only API keys for your CRM and call recording system. We deliver a data flow diagram and a technical specification for the build.
Core Build (Week 2)
We build the data pipeline and core AI logic. You receive access to a private GitHub repository to see the code as it is being written.
Integration and Testing (Week 3)
We connect the AI pipeline to your live systems. You receive a staging environment to test summaries and follow-up drafts on a sample of 20 calls.
Deployment and Handoff (Week 4)
We deploy the system to production on your infrastructure. You receive a runbook with deployment instructions and a 90-day support plan.
Frequently Asked Questions
- What does a typical project cost?
- Pricing depends on the number of systems to integrate and the complexity of the AI logic. A system that summarizes calls is simpler than one that also scores leads based on call content. Most projects are a fixed-price engagement defined after a discovery call. We provide a detailed proposal outlining the scope and total cost before any work begins.
- What happens if the Claude API goes down?
- The system is built with resiliency. If the Claude API is unavailable, the pipeline retries up to 3 times with exponential backoff. If it still fails, the original transcript is logged to a 'failed processing' folder in your S3 bucket and an alert is sent to Slack. No data is lost. We can manually re-process the failed jobs once the API is back online.
- How is this different from buying a tool like Gong?
- Gong is an excellent platform for conversation intelligence with per-user pricing. Syntora builds a targeted automation tool that you own. We focus only on the automation you need, like call summaries or follow-up drafts, without the extra platform features. This results in a lower total cost of ownership and a system tailored to your specific sales workflow.
- Does my sales data leave our infrastructure?
- No, with one exception. The audio is sent to a transcription service and the transcript is sent to the Claude API for processing. The results are immediately sent back and stored in your systems. The source data and the AI outputs are never stored by Syntora. The system is deployed entirely within your own AWS account.
- What kind of maintenance is required after launch?
- The system is serverless, so there are no servers to manage. The main tasks are rotating API keys annually and occasionally tweaking the AI prompts if your sales process changes. The included 90-day support covers any initial adjustments. After that, we offer a simple monthly retainer for ongoing support and maintenance if needed.
- How accurate are the AI summaries?
- The quality depends heavily on prompt engineering, which is where we focus. We tune prompts based on your best-performing reps' examples. Summaries are typically 90-95% accurate for capturing key facts and action items. The drafted emails are designed as a starting point, requiring a 30-second review by the rep, not a complete rewrite.
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