Hire a Pro: RingCentral to Karbon

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1

Request for Proposal (RFP)

RingCentral to Karbon Integration via Make

Project Overview

Montgomery CPA, LLC is seeking an experienced Make automation consultant or agency to design and implement an automated integration between our RingCentral phone system and Karbon practice management platform.

The objective of this project is to automatically capture client communications—including phone calls, voicemails, SMS messages, and call recordings—and create organized, searchable entries within the appropriate client timeline in Karbon.

This project represents the first phase of a larger firm-wide AI automation initiative.

About Our Firm

Montgomery CPA, LLC is a growing CPA firm located in Albuquerque, New Mexico.

Current technology stack includes:

  • Karbon

  • RingCentral

  • Make

  • OpenAI

  • Dropbox

  • Google Workspace

  • Otter.ai

  • QuickBooks Online

Future phases will include deeper integrations between these systems.

Project Goals

Our primary objectives are to:

  • Eliminate manual logging of client communications

  • Create a complete communication history within Karbon

  • Improve staff awareness of prior client interactions

  • Reduce time spent searching across multiple systems

  • Prepare the foundation for future AI-powered workflows

Scope of Work

The consultant will design and implement a Make automation that performs the following functions.

1. Phone Calls

For every inbound and outbound phone call:

Capture:

  • Caller phone number

  • Call direction

  • Date/time

  • Duration

  • Staff member

  • Call recording (if available)

Create a timeline entry in the appropriate Karbon client.

2. Voicemails

For every voicemail:

Capture:

  • Audio file

  • Voicemail transcript (RingCentral or AI generated)

  • Date/time

  • Phone number

Create a Karbon timeline entry.

3. SMS Messages

Capture inbound and outbound SMS conversations.

Include:

  • Date/time

  • Sender

  • Recipient

  • Message contents

Create timeline entries within Karbon.

4. Call Recordings

If a recording exists:

Store a secure reference or link.

Include that reference in the Karbon timeline.

5. Contact Matching

Automatically match communications using:

Primary key:

  • Phone number

Future enhancements may include:

  • Email

  • Client name

  • AI matching

If no client match is found:

Create an exception queue for manual review.

No communication should be be discarded.

6. Timeline Format

Karbon timeline entries should contain:

Communication Type

Examples:

  • Incoming Call

  • Outgoing Call

  • Voicemail

  • SMS

Communication Details

Including:

  • Date/time

  • Duration

  • Phone number

  • Staff member

Transcript (when available)

Recording link (when available)

Make Requirements

The solution must be implemented using Make wherever practical.

If custom API modules are required for Karbon, they should be fully documented.

The completed scenarios, custom modules, and related documentation shall become the property of Montgomery CPA, LLC.

Security Requirements

Because we are a CPA firm, security is critical.

The consultant should explain:

  • Authentication methods

  • Credential storage

  • Encryption

  • Error handling

  • Logging

  • Protection of confidential client information

  • Best practices for securing communications and API integrations

Documentation Required

Project documentation should include:

  • Solution architecture diagram

  • Make scenario documentation

  • API documentation

  • Variables and configuration settings

  • Error handling procedures

  • Ongoing maintenance procedures

Training

Provide one remote training session covering:

  • Scenario operation

  • Monitoring

  • Error recovery

  • Updating credentials

  • Basic troubleshooting

Desired Qualifications

Experience with:

  • Make

  • RingCentral APIs

  • Karbon API

  • OpenAI integrations

  • REST APIs

  • Professional services automation

  • Accounting firms (preferred)

Please include examples of similar projects.

Proposal Should Include

  • Company background

  • Relevant experience

  • Proposed architecture

  • Estimated timeline

  • Fixed-fee estimate (preferred)

  • Hourly rates for future enhancements

  • Ongoing support options

Timeline

Preferred project start:

Immediately

Desired completion:

Within 30 days

Future Opportunities

The selected consultant will receive first consideration for future phases, including:

  • Otter.ai integration

  • Gmail integration

  • Dropbox integration

  • AI meeting summaries

  • AI-generated client notes

  • AI-generated Karbon tasks

  • Firm-wide knowledge search

  • Additional workflow automation

This initial project is intended to establish a long-term relationship with a trusted automation partner.

Proposal Submission

Please include:

  • Estimated project cost

  • Estimated completion date

  • Proposed implementation approach

  • Links to relevant automation projects or case studies

  • References, if available

2 Likes
2

Hey @Montgomery_CPA,

Have sent you a DM as well. Would love to help you set up this RingCentral to Karbon integration. It’s a solid first phase to kick off the bigger AI initiative you mentioned, and exactly the kind of work I do day to day.

I run an AI studio called Automation Jinn where we help firms leverage AI and automate their processes. I am Make advanced certified with a background in computer science, so quite comfortable integrating APIs and custom code. That helps here since Karbon has no native Make app and its timeline entries will need a custom API module, which you already flagged in your brief. I have experience working with both SMBs and large enterprises.

I’ve read through your scope and it’s all very doable in Make. Capturing calls, voicemails, SMS and recordings from RingCentral, matching them to the right client, and creating clean timeline entries in Karbon, with an exception queue so nothing slips through unmatched.

And since you’re a CPA firm, I know security is the top priority, so I’d build this to keep client data protected and access tightly controlled throughout. Happy to walk your team through how that works.

Some of my relevant work:

  • Built a smart call-routing system with Twilio and Airtable to automate lead handling (directly relevant telephony/CRM logic).
  • Set up Quo (formerly OpenPhone) as the VOIP system for a bakery brand and automated the workflows around it, including missed-call auto-text and 10DLC registration for compliant business texting.
  • For a 500+ employee company, built end to end AI agents in Make with robust error handling, cutting asset creation from hours to minutes.

I work more as an AI transformation partner for my clients rather than just a builder, so the multi phase setup you’re describing (Otter, Gmail, Dropbox, AI notes down the line) is right up my alley.

Your 30 day window is very doable, I’d estimate roughly 2 to 3 weeks for this first phase. The exact fixed fee quote really depends on the final scope (call volumes, Karbon API access, storing vs linking recordings), so would love to jump on a quick call to pin that down and give you a firm number.

Happy to jump on a call if it’s easier: https://cal.com/sparsh-gupta-pnrp6p/30min, or just reply to my DM.

Cheers,
Sparsh
Founder
Automation Jinn

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Hello @Montgomery_CPA
Instead of just describing how I’d build it, I put together a working demo of your exact use case. It captures sample calls, voicemails, and SMS, matches each to the right client by phone number, writes a clean timeline entry, and routes anything unmatched to a review queue so nothing gets discarded.

See it running here: [ https://jocular-unicorn-c0a32d.netlify.app/]

The phone matching, exception routing, and timeline formatting you’ll see are the real output of the tested logic, on invented sample data no live keys, nothing touching your systems.

Quick overview of my approach: a Make scenario triggered by RingCentral events, normalize the phone number, match against your client directory, write the formatted entry to the correct Karbon client, and log every run. Unmatched comms go to an exception queue for manual review. Phone is the primary key now, and it extends cleanly to email or AI matching in your later phases.

On security (since you’re a CPA firm): OAuth 2.0 for both platforms, credentials in Make’s encrypted store never in the scenario body, TLS in transit, recordings referenced by secure link, error routes with retry-then-log so nothing is lost, and a full audit trail.

Everything becomes your property scenarios, custom modules, full documentation, plus a training session. I can deliver within your 30-day window and start right away.

Would love to be your long-term automation partner on this. Happy to walk through the demo on a call.

:globe_with_meridians: Website: https://www.pathfinderautomationsolutions.com
:date: Book a call: Calendly
:briefcase: Upwork: https://www.upwork.com/freelancers/~01446d60f782215efa
:e_mail: Email: [email protected]

Taiwo
CEO, Pathfinder Automation Solutions

4

Hi Montgomery CPA Team,

This is exactly the kind of integration I specialize in.

I build business automation systems with Make, connecting platforms through APIs while keeping security, documentation, and long-term maintainability in mind. I’ve worked on workflows involving CRMs, communication platforms, AI services, and custom REST API integrations, including OpenAI-powered automations, exception handling, logging, and structured data synchronization.

For your project, I’d implement a Make-based solution that:

  • Automatically captures RingCentral calls, voicemails, SMS, and recordings.
  • Matches communications to the correct Karbon client using phone numbers, with an exception queue for unmatched records.
  • Creates consistent, searchable timeline entries with transcripts and recording links where available.
  • Includes robust error handling, monitoring, and documentation for future maintenance and expansion.

I’m also comfortable documenting custom API calls, providing training, and designing the solution so it’s ready for future phases like Gmail, Dropbox, Otter.ai, and AI-generated client summaries and tasks.

I’d be happy to discuss your requirements in more detail and provide an implementation plan, timeline, and fixed-fee estimate.

You can reach me at [email protected].

I look forward to hearing from you.

5

Hi — I read your post closely, and the detail that stood out to me is the one most people would skip: you don’t just want calls and SMS logged into Karbon, you need the system to know when it *isn’t* sure — a proper “no client match found” path — because a misfiled communication in a CPA firm is worse than no entry at all.

That safeguard is the backbone of what I’ve designed for you, and I’ve put the whole thing in a short proposal (attached).

A few things it covers:

• Real-time capture of calls, voicemails, transcripts and SMS via RingCentral webhooks (no native Karbon connector needed — I build the API integration directly)

• Automatic phone-number matching to the right Karbon client, with the exception queue for anything uncertain

• A full, audit-ready trail of every communication

And because you’re a CPA firm handling confidential financial data, I made security the core of the proposal rather than a footnote — credential encryption, OAuth/JWT, TLS + AES-256, webhook verification, least-privilege access, and an immutable audit log. It’s Section 3 if you want to jump straight there.

Fixed price and a phased 3-week plan are inside, along with a no-risk first step: I’ll record a short screen walkthrough on a sandbox so you can see the exact data flow before committing anything.

Happy to answer any technical questions right here in the thread.

— Hamza (AXONA)

Montgomery_Proposal_RingCentral_Karbon_2026-07-09.pdf (107.3 KB)

6

Hi Montgomery_CPA,

I saw your RFP for the RingCentral to Karbon integration and wanted to follow up.

My colleague has already reached out regarding this opportunity but wasn’t able to connect, so they left a voicemail and sent over our proposal for your review.

At Flowbird Ltd, we specialise in Make.com automation and complex system integrations, including API-driven workflows, AI integrations, and secure data processing for businesses where reliability and data protection are critical.

Your project aligns closely with the type of automation solutions we deliver, and we’d be keen to explore how we can support both this initial integration and the wider AI automation roadmap you have planned.

If you have any questions about the proposal or would like to discuss the approach in more detail, we’d be happy to arrange a conversation. You can reach out to my colleague via the ema

Many Thanks,

Roshan
Flowbird Ltd

7

Hi @Montgomery_CPA,

Welcome to the Make Community!

This is one of the most well-structured RFPs I’ve seen here.

Your approach of building a reliable communications layer first before expanding into AI-powered workflows makes a lot of sense, especially for a CPA firm where traceability, auditability and security are critical.

I’ve built Make.com automation projects involving complex API integrations, OpenAI workflows, webhook orchestration, validation layers and business process automation. I also have experience designing modular workflows that can be extended over time rather than becoming difficult to maintain.

A few questions that would help shape the implementation:

• Are you already using the Karbon public API, or are there any existing custom integrations in place?
• Will RingCentral webhooks be available for real-time events, or should the solution also account for scheduled synchronization?
• Would you prefer the exception queue to remain inside Karbon, or would you rather manage unmatched communications through Airtable, Google Sheets, or another review interface?

I’ve also sent you a DM with my portfolio, recent automation projects and contact details.

I look forward to learning more about the project.

8

Hi — this is a clean fit for how I build in Make. The core here isn’t the happy path (call comes in, match by number, drop a Karbon timeline entry) — it’s the messy 15%: numbers that don’t match a client, shared or spoofed caller IDs, voicemails with no transcript yet, and making sure a CPA firm’s data never lands on the wrong client record.

How I’d wire it:

  • RingCentral side: subscribe to call/SMS/voicemail events over their webhooks, pull duration, direction, staff extension, and the recording URL.
  • Matching: normalize the number and look it up against Karbon contacts. Clean match → timeline entry. No match or multiple matches → an exception queue a human clears, so nothing gets filed to the wrong client silently.
  • Karbon side: one consistent timeline note per communication — type, who, when, transcript if there is one, and a link to the recording.
  • Errors: retries with backoff on the API calls, and a failed item waits in review instead of vanishing.

I do a lot of exactly this shape of work — pull messy inputs from one system, apply the matching rules, and flag anything the rules can’t resolve for a person instead of guessing. The OpenAI phase later (transcript summaries, call categorization) drops in over the same pipeline.

Two things before I scope it properly:

  • Karbon: are you on their API tier, and do you want the note on the Client record, the Work item, or both?
  • Roughly what call volume per day, so I size the matching and the exception review right?

Happy to keep it all in writing here so you’ve got a record of the decisions.

9

Hi Montgomery CPA team,

The Karbon module isn’t the risky part of this build — the phone number is. Your exception-queue + audit-trail language points at the same failure: a partner opens Karbon and finds one client’s history split across two records because RingCentral retried a webhook or the client changed numbers mid-engagement. That misrouted call is the error partners notice first and clients never forgive.

A polished demo shows the happy path. What breaks a small CPA firm in month 3 is the exception queue misfiring and no one owning the fix.

Day-one: E.164 normalization + a client-alias table so a number change doesn’t orphan history. Dedupe on RingCentral call UUID + ingest timestamp so a redelivered webhook can’t double-log. Exception queue surfaces only genuine ambiguity — human-reviewable, not a firehose partners ignore. No client PII leaves the Karbon sandbox until go-live.

Redacted handoff doc from a US healthcare consulting build (NDA): Handoff Sample — n8n Automation Delivery — Priyanshu Kumar. Related row-level access + audit trail: AiXpert — AI Database Assistant.

US business hours, sub-24-hour SLA when Karbon breaks in month 6 — written into the SOW.

20-min call this week. Reply with your email — Phase-1 SOW + fixed fee within 48 hours. On signed SOW: working RingCentral-to-Karbon prototype on a Karbon sandbox in 10 business days — custom module, phone-match, dedupe, exception queue, audit log.

— Priyanshu Kumar / AI & Automation Engineer / priyanshukumar.co

10

Proposal: RingCentral–Karbon Communication Logging Automation

Prepared for: Montgomery CPA, LLC Prepared by: Effinyx Technologies (effinyx.com) Date: July 12, 2026

1. Understanding of the Requirement

Montgomery CPA needs every client-facing communication that touches RingCentral — calls, voicemails, SMS, and recordings — to land automatically in the correct Karbon client timeline, with nothing falling through the cracks and nothing requiring manual entry. This is not a simple “connect two apps” job: it requires reliable contact matching, an exception path for unmatched communications, secure handling of confidential client data, and a build that a non-technical team can operate and troubleshoot after handoff. We’ve scoped this proposal around exactly that, not a generic Make template.

We also understand this is Phase 1 of a longer automation roadmap (Otter.ai, Gmail, Dropbox, AI-generated notes and tasks). We’ve architected the scenario set so those future phases plug in without rework — details in Section 4.

2. Proposed Architecture

Platform: Make.com, orchestrating RingCentral and Karbon via a set of purpose-built scenarios rather than one monolithic flow. This keeps error handling isolated (a Karbon API hiccup on SMS logging won’t stall call logging) and makes future maintenance easier.

Scenario breakdown:

Scenario Trigger Function
Call Logger RingCentral webhook (call ended) Pulls caller number, direction, timestamp, duration, staff extension, recording URL; matches contact; writes Karbon timeline entry
Voicemail Logger RingCentral webhook (voicemail received) Pulls audio file + transcript (native RC transcript, or routed through OpenAI Whisper if RC transcription is unavailable/low-confidence); matches contact; writes Karbon timeline entry
SMS Logger RingCentral webhook (SMS received/sent) Captures full thread metadata and message body; matches contact; writes Karbon timeline entry
Contact Matcher (shared module) Called by the three loggers above Normalizes phone number format, queries Karbon contacts by phone; returns match or “unmatched” flag
Exception Handler Triggered on unmatched or failed writes Logs the full communication payload to a review queue (Google Sheet or Karbon “Unassigned” work item — your preference) with the raw data intact, and notifies a designated staff member

Why separate scenarios instead of one big flow: if Karbon’s API is briefly unavailable, you don’t lose call logging while SMS logging is also down — each recovers independently, and Make’s built-in retry/error logic is scoped to the failure that actually occurred, not the whole pipeline.

Contact matching logic: phone number is the primary key, normalized to E.164 format before lookup to avoid false negatives from formatting mismatches (a common failure point in these integrations). Every unmatched communication is preserved — nothing is discarded — and routed to a manual review queue so your team can either match it manually or flag it as non-client (e.g., vendor calls, spam).

Karbon timeline entry format: each entry follows a consistent template — Communication Type, Date/Time, Duration (calls), Phone Number, Staff Member, Transcript (when available), and a secure link to the recording (when available) rather than embedding the file directly, keeping Karbon entries lightweight and load times fast.

3. Security & Compliance Approach

We treat this as a CPA-firm-grade build from day one, not a bolt-on:

  • Authentication: OAuth 2.0 for both RingCentral and Karbon (no static API keys stored in scenario modules). Refresh tokens are held in Make’s encrypted connection vault, not in scenario variables.
  • Credential storage: All credentials live in Make’s native connections manager, scoped to the minimum permissions each scenario needs (least-privilege access) — call/SMS/voicemail read access only, no unnecessary write scopes on either platform.
  • Encryption: All data in transit uses TLS via the native RingCentral and Karbon connectors; recording links are shared as secure, permission-gated references rather than public URLs.
  • Error handling: Every scenario has structured error handlers (not just Make’s default “ignore and continue”) — failures are caught, logged with full context, and routed to the Exception Handler rather than silently dropped.
  • Logging: A dedicated execution log (Google Sheet or Airtable) tracks every run, its outcome, and any manual interventions required — giving you an audit trail independent of Make’s own history retention.
  • Confidentiality: No client communication content is routed through any third-party service beyond RingCentral, Karbon, and (where transcription assistance is needed) OpenAI’s API under a business-tier agreement with no training-data retention.

4. Foundation for Future Phases

Because contact matching, error handling, and the Karbon-write module are built as reusable components (not hardcoded per-scenario logic), extending this into Otter.ai meeting summaries, Gmail logging, or AI-generated Karbon tasks later means adding new trigger scenarios that call the same core modules — not rebuilding matching and logging logic from scratch. This is a deliberate architectural choice given the phased roadmap you’ve described.

5. Documentation & Handoff

You’ll receive, in full and as your property (per the RFP’s ownership terms):

  • Solution architecture diagram (scenario map + data flow)
  • Per-scenario documentation: trigger conditions, field mappings, error paths
  • API documentation for any custom Karbon modules built beyond the native connector
  • A configuration reference (variables, connection names, exception queue location)
  • A written maintenance procedure covering credential renewal, monitoring, and common failure recovery
  • One live remote training session (recorded for future reference) covering scenario operation, monitoring, error recovery, credential updates, and basic troubleshooting

6. Timeline

Phase Duration Milestone
Discovery & API validation Days 1–3 Confirm RingCentral webhook access, Karbon API scopes, contact data quality
Core build (Call, Voicemail, SMS loggers + Contact Matcher) Days 4–7 Working end-to-end flow in a sandbox/test environment
Exception handling & testing Days 8–10 Live testing against real call volume, edge-case handling
Documentation & training Days 10-12 Delivery of documentation, live training session
Buffer / go-live support Days 12-15 Monitoring during first week of production use

This fits within your requested 15-day completion window, with discovery starting immediately upon engagement.

7. Ongoing Support Options

  • Ad hoc, hourly, as issues arise
  • Monthly maintenance retainer covering monitoring, credential renewal, and minor adjustments — quoted separately on request

8. Next Steps

We’d welcome a short discovery call to confirm RingCentral webhook access on your account tier and review your current Karbon contact data structure both directly affect the contact-matching accuracy discussed in Section 2. Happy to start immediately upon agreement.

Effinyx Technologies [email protected] | effinyx.com

11

Montgomery CPA team, TinyOps Studio LLC can deliver this as a fixed $4,800 implementation, with completion within 30 calendar days of receiving API access and the approved field map. The kickoff milestone would be 40%, with the balance tied to tested acceptance criteria and handoff.

The Make architecture would use RingCentral event notifications plus a reconciliation pass for completed calls, SMS, voicemail, transcripts, and recording metadata. Each event would be normalized to a stable communication ID and E.164 phone number, matched against Karbon Contacts through the API, and written as a structured contact-linked Karbon note. Unmatched or ambiguous numbers would go to an exception queue; retries would update the same record instead of duplicating client history.

For security, I would use least-privilege RingCentral and Karbon credentials, keep secrets in managed Make connections, avoid putting audio or client content into scenario logs, and store only a permission-checked recording reference unless you approve a separate retention location. Delivery includes an architecture diagram, scenario and custom HTTP-module documentation, configuration inventory, error/retry runbook, acceptance test evidence, and one remote operator training session.

TinyOps builds API-connected workflow systems for small-business operations and has a working Vapi/Twilio voice-workflow reference implementation plus documented webhook, CRM-style routing, retry, and exception-handling patterns. I have not implemented this exact RingCentral/Karbon pairing before, so I would make API-access validation and one end-to-end call-to-note slice the first acceptance checkpoint rather than overstate platform-specific experience.

Proposed schedule: days 1-3 access and field-map validation; days 4-10 call/SMS ingestion and Karbon matching; days 11-18 voicemail, transcript, and recording handling; days 19-24 exception routing and security hardening; days 25-30 acceptance testing, documentation, and training. Future enhancements are $150/hour; optional monitoring and monthly health reporting are $350/month. If the RFP is still open, please DM TinyOpsStudio and I will send the short implementation brief and acceptance matrix.

12

I have installed several of these services into multiple medical practices that can do what you want plus more! and since you have ring central that perfect because we work with them. Ill semd you a dm.

13

Hi, this is a well-specified RFP, which makes it easier to reason about. Let me be upfront: I’ve built complex multi-branch Make scenarios (webhook triggers, HTTP calls to custom backends on AWS Lambda, multi-source Notion sync, routers with success/error handling, two-way calendar sync), but I have not yet built against the Karbon or RingCentral APIs specifically. Karbon has no native Make module, so this would be custom API modules either way, documented as you require.

A few questions to scope the proposal accurately:

  • Does RingCentral push call/SMS events via webhook, or would this be polling on a schedule?
  • For Karbon, do you already have API access provisioned, or is that part of the scope?
  • The contact-matching exception queue: is a simple Make data store / Google Sheet acceptable for manual review, or do you want it inside Karbon?

Happy to share a walkthrough of a scenario I’ve built so you can judge the technical level directly. If the fit is right on experience, I’d propose a fixed fee with a transparent rate given this would be my first build against your exact stack.

14

@Montgomery_CPA hey! ringcentral → karbon is a classic custom integration since make doesn’t have a native karbon module.

the cleanest way is setting up a custom webhook in ringcentral for call/sms events, then using make’s “make an api call” module (or HTTP request) to hit karbon’s REST API /v1/tasks or /v1/contacts endpoints. for phone number matching, you just do a quick lookup in karbon first before creating a new work item.

i build custom API integrations on make for CRMs without native modules. drop me a DM if you want to get this set up.

15

Hi Montgomery CPA team,

Proposal per your RFP structure.

Background: solo automation engineer. I build data pipelines and automations daily for a lead generation firm, and I run my own production systems end to end. You would work directly with the person building, no agency handoff.

Relevant experience, three builds that map onto your phases:

  1. An AI receptionist for small businesses that handles inbound calls it captures: caller details, timestamps, transcripts and query logging, with a tested API behind it. That is your exact data shape, phone communications turned into structured, searchable records.

  2. A production document pipeline I run solo: multiple API sources plus a scraper, LLM classification behind a tested eval suite, daily unattended runs via CI. Code: GitHub - Manveen07/tender-radar-showcase · GitHub , walkthrough: tender-radar | Loom . Same skeleton as this project: events in, matching logic, clean writes out, nothing dropped silently.

  3. AsanaBot, an automation that creates and manages tasks in a practice management tool from upstream events. Relevant because your future phases list AI generated Karbon tasks, which is the same pattern against a different API.

Proposed architecture, short version: RingCentral webhooks trigger Make scenarios per communication type. Phone numbers normalized to E.164 and matched against Karbon contacts. Karbon has no native Make app, so timeline entries go through custom HTTP modules against their REST API, fully documented and yours to keep per your ownership requirement. Recordings stay in RingCentral and are linked, not copied, so confidential audio never sits in a third system. Two details most proposals skip: an exception queue where unmatched communications get parked with full context for manual review (your “no communication discarded” line), and idempotent writes keyed on the communication ID so a retry never creates duplicate timeline entries.

Before you commit to anyone: I will send you a one page exception handling and security design doc for this exact spec, free, within 48 hours of you replying. Judge the thinking before spending anything.

Security: OAuth where supported, credentials in Make’s connection vault only, least privilege API scopes, full scenario logging, and the design doc covers each of your listed security questions in writing.

Fixed fee: $1,200 including documentation, architecture diagram and the training session. Timeline: design doc first, working build within 2 weeks of access, complete within your 30 day window. Future enhancements at $40/hr. 30 days of post delivery fixes included.

Honest notes: this would be my first Karbon integration specifically (the custom module gets documented precisely because of that), and I am a solo builder, not a certified agency. What you get is the builder’s full attention and a price without agency overhead.

Manveen

17

Hi @Montgomery_CPA,

Phone and messaging automation is my daily work. I run a live AI receptionist line that answers calls and texts, books appointments, and logs every call with a transcript through webhooks. You can test it right now: 760 437 6082. That loop, capture the event, transcribe, match the caller, write a clean record, is exactly what this RFP asks for, just pointed at Karbon instead of my own stack.

Proposed architecture:

  1. RingCentral webhook subscriptions for calls, voicemails, and SMS into Make.
  2. One normalizer scenario producing a standard record per event: type, direction, date/time, duration, staff member, links.
  3. Contact match on phone number against Karbon contacts. No match goes to an exception queue for manual review, nothing gets discarded.
  4. Custom HTTP modules for Karbon timeline entries, fully documented and owned by your firm.
  5. Recordings stay in RingCentral and are referenced by secure link. Voicemail transcripts via RingCentral or OpenAI.

Security: OAuth connections in Make’s credential vault, no client data stored outside your systems, error handlers with retries and alerts on every scenario.

Fixed fee: $1,850 including the architecture diagram, full documentation, a remote training session, and 30 days of post launch fixes. Done inside 14 days. Future phases at $65/hr.

Blaz
Blaz Algo Systems, blazalgosystems.netlify.app

18

Hi Montgomery CPA team,

I can help with the RingCentral-to-Karbon Make integration and would be happy to propose a fixed-fee phase one.

My approach would be to capture RingCentral calls/messages, match them to Karbon contacts or clients, create clean timeline notes/tasks with timestamps and source details, and add an exception queue for unmatched numbers, duplicates, or failed syncs.

I’d also make sure the workflow has secure logging, clear documentation, and is maintainable by your team after handoff. I’d keep the first phase practical, while leaving the architecture ready for later QuickBooks Online and broader firm automation.

If you’re still accepting proposals, please send over the RFP/details and I can respond with an implementation plan, timeline, and fixed-fee estimate.

Best,

Marina

SAHAR Studio

19

Hi @Montgomery_CPA — following your RFP structure:

Background. Independent automation engineer, 20+ years of ERP and accounting-system integration. I’ve spent my career building integrations that accountants trust: clean audit trails, no silently dropped records, documentation the next person can maintain. Last two years: Make/n8n plus LLM application work (Claude API daily).

Relevant experience. I run a production field-reporting system built on exactly the pattern your RFP describes: events matched deterministically to records, everything unmatched goes to an exception queue, nothing discarded, and billing documents are generated from the same database — case study: Claude Artifact . On the AI side: a quoting agent for a Swiss client with strict “never invent data” guardrails — directly relevant to your future phases (AI meeting summaries, AI client notes), where hallucinated content in a client file is unacceptable.

Proposed architecture. RingCentral webhook subscriptions (calls, voicemails, SMS) → one normalizer scenario producing a standard event record → phone matching against Karbon contacts with E.164 normalization, dedupe and multi-number handling → documented custom HTTP modules writing Karbon timeline entries (type, direction, timestamp, duration, staff member, transcript, secure recording link) → exception queue with manual review and retry. OAuth in Make’s credential vault, error handlers with alerts on every scenario, full logging; recordings stay in RingCentral, referenced by link.

Timeline. 10–14 days from access.

Fixed fee. $1,200 — including architecture diagram, scenario and API documentation, configuration reference, error-handling runbook, one remote training session, and 30 days of post-launch fixes.

Future enhancements. $30/hr. Your roadmap (Otter.ai, AI summaries, AI-generated notes, knowledge search) is my core specialty — happy to sketch the phase-2 AI architecture during phase 1 at no extra cost.

Ongoing support. Pay-as-you-go at $30/hr, or a light monitoring retainer at $120/month (weekly checks, alert response).

Working style: async and in writing, documentation-first; my working hours cover your business mornings for same-day replies.

Alexander

20

Two things in this RFP deserve more attention than the connector list, because they decide whether the timeline entries are trustworthy:

First, matching. The join key between a RingCentral event and a Karbon client is a phone number, and phone numbers are messy — shared office lines, spouses, formatting variants. The build needs an explicit mapping table plus a defined “unmatched” lane that routes to a human review queue instead of guessing. A timeline entry filed under the wrong client is worse than no entry.

Second, recordings. Call audio should not live inside Karbon; the durable pattern is recordings archived to storage you control with a stable reference in the Karbon timeline note, so entries stay searchable and storage stays yours.

Both are design decisions, not code volume, which is why I would scope this as a short written design doc first (fixed price), then fixed-price per phase against it. That also gives your future AI phases a foundation document instead of an undocumented scenario.

I work fixed-price per deliverable, async, CET, written briefs over meetings.

21

Hi Montgomery CPA team, I read the RFP. The safest first phase would be to map the RingCentral event types, phone number matching, recording and transcript references, and the unmatched exception queue before writing anything into Karbon.

I would then prove one call, one voicemail, and one SMS through a controlled test path. I have built review first automation systems with run history, controlled actions, and evidence based QA, but I would not claim prior RingCentral to Karbon production delivery.

I can send a contained validation scope covering architecture, security approach, matching rules, failure handling, and test evidence before a full implementation quote. Worth sending over?