Mike HeapMike is an experienced Product Manager who focuses on all the “non-development” areas of My AskAI, from finance and customer success to product design, copywriting, testing and more.
Table of Contents
- What AI can I use to reply to customer support tickets, My AskAI or Decagon?
- How does an AI customer service agent work, My AskAI vs Decagon?
- What are the different ways I can use an AI agent: direct, copilot, internal notes, voice?
- Direct replies
- Copilot replies
- Internal note replies
- Voice
- Which is easier to setup, Decagon or My AskAI?
- How do My AskAI and Decagon differ in what they can be trained on?
- 'Static' content
- 'Dynamic' content
- Which has better answer quality, Decagon or My AskAI?
- Which AI agent is easier to improve over time: Decagon or My AskAI?
- Which has more features, Decagon or My AskAI?
- Is it easy to customize My AskAI and Decagon?
- What about vendor lock-in?
- Does Decagon or My AskAI have any other AI features?
- Tagging
- Agent translation
- Sentiment, QA and fraud monitoring
- What about security, is Decagon more secure than My AskAI?
- Which costs more, Decagon or My AskAI?
- The pricing model
- The overall cost
- Conclusion - should I choose Decagon or My AskAI?
- FAQs
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My AskAI and Decagon both run an autonomous AI agent for customer support, but they aim at opposite ends of the market. Decagon is enterprise-only and sales-gated, an "AI concierge" built for names like Chime, Notion and Duolingo that field huge support volumes across chat, voice, email and SMS. My AskAI goes the self-serve route: you connect it to the helpdesk your team is already running, and its per-ticket rate is one you can switch on the same day. Pick Decagon for voice and omnichannel at enterprise scale with the deepest compliance grid in the category; pick My AskAI for transparent pricing, fast setup, and mid-market fit.
Decagon won't name a price without a sales call, and outside contract data pegs its typical deal near $433,000 annually. My AskAI runs about $0.10 a ticket, goes live on your existing helpdesk within the week, and lets you rehearse it on your historical tickets during a 30-day trial before you spend a penny.
I'm Mike, co-founder of My AskAI. We help 200+ ecommerce and SaaS businesses run AI customer service inside the helpdesk they already use, and our agents have resolved more than a million tickets between them. So I'll flag up front where I'm biased, and I'll be just as plain about where Decagon is the better choice, because for a good chunk of readers it is.
What AI can I use to reply to customer support tickets, My AskAI or Decagon?
TL;DR: Both are autonomous AI agents that resolve tier-1 tickets. My AskAI installs inside your existing helpdesk (Zendesk, Intercom, HubSpot, Freshdesk, Gorgias); Decagon is a standalone enterprise platform that sits above your helpdesk and connects to Zendesk, Salesforce, Intercom and Kustomer (no Freshdesk).
Both products solve the same headline problem, an AI agent that answers the repetitive customer questions so your team doesn't have to, but they're built on opposite assumptions about who's buying.
My AskAI is an AI agent that lives inside the helpdesk you already run. You install it from the marketplace of Zendesk, Intercom, HubSpot, Freshdesk or Gorgias, point it at your knowledge, and it starts drafting and sending replies on your existing tickets.
It isn't a helpdesk and never becomes one. It replaces the native AI agent inside your helpdesk (Fin, Zendesk AI, Freddy, Gorgias Automate, Breeze), at roughly $0.10 a ticket.
Decagon takes the other road. It's a standalone enterprise "AI concierge" that sits above your stack.
It connects by direct API to Zendesk, Salesforce, Intercom and Kustomer, running the AI layer while your helpdesk keeps doing the human-agent ticketing. There's no Freshdesk connector and no helpdesk-marketplace listing (every integration is a wired API).
Decagon is built squarely for the enterprise: it serves 100+ enterprise customers and 10M+ end customers, and it's built for organizations fielding very high volumes, with a qualification bar reported to sit up in the hundreds of thousands of conversations a year. If your volume is well under that, you're not really who they're pitching to. That's a deliberate choice on Decagon's part, and I don't hold it against them.
Both products review well on G2:
My AskAI | Decagon | |
Rating | 4.5 / 5 | 4.9 / 5 |
Reviews | 21 | 18 |
Reviews page |
Decagon's 4.9 edges our 4.5, and both are strong scores. Either way, this comparison comes down to which agent fits how your team runs.
How does an AI customer service agent work, My AskAI vs Decagon?
TL;DR: Same core loop, ingest your knowledge, answer the customer, take an action, escalate to a human when needed. Decagon's signature is Agent Operating Procedures, support workflows written in plain language that compile into code and run on a multi-agent stack with a supervisor model that catches hallucinations. My AskAI focuses that loop on the helpdesk ticket and teaches itself from your agents' replies.
Under the hood, both agents run the same basic loop. You connect knowledge, the agent reads an incoming question, it answers what it can, it takes a structured action where one's configured, and it escalates what it can't handle to a human with a summary so nobody has to repeat themselves.
Decagon's version of that loop has a differentiated piece of design at its center: Agent Operating Procedures (AOPs). These are support workflows written in natural language that, in Decagon's words, "combine the flexibility of natural language with the precision of coded logic" and compile into code the agent then executes reliably.
On top of that, Decagon runs a multi-model, multi-agent stack: an ecosystem of agents (built on OpenAI, Anthropic and Cohere models plus fine-tuned ones) that review each other's work, with a supervisor model that detects hallucinations before a response goes out and revises them. The AOP-plus-supervisor design is a thoughtful piece of engineering.
My AskAI's loop is narrower on purpose. It sits on the ticket, answers inside your helpdesk's own chat, messaging or email channel, and then reads what your human agents wrote after a handover and drafts fresh knowledge from it.
That's Self-Learning, and it means the resolution rate climbs over time without anyone sitting down to retrain it. We run a suite of models too (OpenAI, with Google and Anthropic where they win on a given task), so neither of us is a one-LLM product.
What are the different ways I can use an AI agent: direct, copilot, internal notes, voice?
TL;DR: Both do direct customer replies and behind-the-scenes copilot drafting. My AskAI adds an internal-note mode for zero-risk testing; Decagon adds voice and SMS, including outbound voice launched in Spring 2026, which My AskAI doesn't offer.
There's more than one way to put either agent to work, and the modes are where each side's personality shows.
Direct replies
Both agents reply directly to customers, and this is the primary mode for each. A question comes in over chat, messaging or email, and the AI answers it end to end, escalating only when it needs a human.
In practice, nothing much separates the two here. It's the standard tier-1 deflection job both were built to do, and I wouldn't pick a winner on it.
Copilot replies
Both also offer a copilot mode, where the AI drafts a reply behind the scenes and a human agent sends it. There's a meaningful difference in reach, though.
Decagon's Agent Assist copilot is restricted to Zendesk only, which G2 reviewers flag as a frustration: it caps how broadly teams can use it across departments. My AskAI's copilot runs across every helpdesk it integrates with, plus a free Chrome Extension copilot that works inside any of our integrated helpdesks, with no per-seat charge.
Internal note replies
This one is a My AskAI exclusive, and the mode I'd point any nervous team toward first. My AskAI can draft its reply as an internal note on every ticket, so it never goes to the customer.
Your team sees the AI's answer side by side with what a human would have said, so you can check quality against whatever AI you already run before you ever go live. It's the zero-risk on-ramp, and Decagon's white-glove model doesn't have a direct equivalent you can switch on yourself.
Voice
Voice is Decagon's exclusive here. Decagon Voice handles inbound calls and, since the Spring 2026 launch, outbound voice too: proactive calls, campaigns, callbacks and voicemail.
It plugs into telephony through Amazon Connect, RingCentral and SIP trunking, and Decagon's fine-tuning work reports sub-400ms model latency so the calls feel responsive. My AskAI has no voice or phone product at all.
If voice is on your list today, that's a genuine reason to look at Decagon.
Which is easier to setup, Decagon or My AskAI?
TL;DR: My AskAI wins clearly. It's self-serve: sign up, connect your helpdesk and knowledge, and you're live in minutes to days, with a 30-day trial you can run against your own past tickets. Decagon is sales-led white-glove: a demo, a discovery phase, a dedicated project manager and forward-deployed engineer, and a roughly six-week phased rollout with no way to test before you engage sales.
This is the sharpest split in the whole comparison.
With My AskAI you sign up with a business email, install the app from your helpdesk's marketplace, and connect your knowledge. Setup runs about 10 to 15 minutes, and teams switching from Fin or Zendesk AI are usually fully over in under a day (no developer needed for the standard setup).
Better still, you get a 30-day free trial with every feature unlocked, unlimited tickets and no card. You can simulate the agent against your own past tickets before it ever replies to a live customer, and I'd use every day of that trial to measure it on your own support before deciding.
Decagon is a different kind of engagement. There's no self-serve signup and no free trial; the only door is booking a demo.
From there it's a sales-led, white-glove rollout: discovery, a dedicated Agent Product Manager plus a Forward-Deployed Engineer, and a documented phased deployment that Decagon's own material describes as around six weeks. There isn't a public docs site to read either, because onboarding is handled hands-on by that assigned team.
The reviews do back up a fast initial stand-up, mind you, with one customer noting implementation was "very quick (under a week) and the team is constantly supportive", though the deeper integrations and more complex procedures still need engineering time. You get a lot of expert hand-holding, but you can't kick the tires without a sales process, and you can't put a price or a resolution number on it before you commit.
How do My AskAI and Decagon differ in what they can be trained on?
TL;DR: My AskAI ingests the modern knowledge stack self-serve (Notion, Google Drive, Confluence, SharePoint, OneDrive, Dropbox, past tickets and help centers) with internal-only marking. Decagon's Unified Knowledge Graph is strong on structured and CRM data (Salesforce, Shopify, Stripe, custom APIs) but has no publicly documented native Notion or Drive upload, since ingestion is handled during onboarding.
Both agents are only as good as what they know, so it comes down to the sources each can pull from.
'Static' content
This is your written knowledge: help centers, product docs, policies, FAQs. My AskAI lets you connect a wide set of sources yourself, no onboarding team required: Google Drive, Notion, Confluence, SharePoint, OneDrive, Dropbox, the Zendesk, Intercom and Freshdesk help centers (including behind-login articles), plus website sync and direct PDF or DOCX upload. You can also mark any file or page internal-only, so it feeds copilot and internal answers without ever surfacing to a customer.
Decagon's Unified Knowledge Graph pulls from help centers and structured knowledge bases (Zendesk, Kustomer, Guru, Confluence, Contentful) and past conversation transcripts. It doesn't publicly document native, self-serve upload from Notion, Google Drive or SharePoint. That ingestion is handled during the white-glove onboarding rather than through a self-serve connector, so you won't find it documented as something you wire up yourself.
'Dynamic' content
This is the live data: order status, account details, subscription state. My AskAI reads live customer data through its User Data API and a native Shopify connector, and it can take actions (refunds, cancellations, order updates) through Tasks and Tools. It also trains on your past tickets, with the last 5,000 resolved tickets backfilled by default (more on request), which is a fast way to bootstrap knowledge if your help center is thin.
Decagon is strong here, and this is where it out-reaches us. Its graph connects to Salesforce Customer 360 CRM records, Shopify and Stripe, internal business APIs for live order and account data, Slack, and custom APIs and MCP, and its AI Actions can execute across those systems. If your support answers depend heavily on reading and writing structured CRM and commerce data, Decagon has done a lot of the plumbing.
Here's the side-by-side:
Source | My AskAI | Decagon |
Help center / KB | ✅ | ✅ |
Past tickets + simulation | ✅ | ✅ (transcripts) |
Notion | ✅ | Not documented |
Confluence | ✅ | ✅ |
Google Drive | ✅ | Not documented |
SharePoint / OneDrive | ✅ | Not documented |
Slack | — | ✅ |
Salesforce / CRM records | Knowledge pages | ✅ (Customer 360) |
Shopify / Stripe | ✅ (Shopify) | ✅ |
Structured KB (Guru / Contentful) | — | ✅ |
Internal-only marking | ✅ | Not documented |
Neither column is a clean sweep. Decagon wins on structured CRM and commerce data; My AskAI wins on the self-serve modern-docs stack and on the bulk historical-ticket simulation you can run yourself (no onboarding call needed).
Which has better answer quality, Decagon or My AskAI?
TL;DR: Roughly equivalent on tier-1 questions from a clean knowledge base. Decagon markets an 80% average deflection rate with case studies spanning 50 to 90%; both products sit around the field median. Treat published rates as loose signals, since every vendor defines the metric its own way.
Answer quality is where marketing numbers fly around, so let me be careful with them.
Decagon markets an 80% average deflection rate and a 93% agent-quality score, and its published case studies span a wide band, from around 50% up to 90% (Substack at 90% resolution, Duolingo at 80% deflection, Chime at 70% across chat and voice). Those are impressive numbers, and they're all Decagon's own, so take them with a grain of salt.
The counterweight is that Decagon's weakest G2 sub-score is Ticket Resolution at 7.9 out of 10, well below its 9.7 for Quality of Support, which suggests real resolution can lag the deflection headline. Decagon says as much itself, warning on its own blog that "high deflection rates can hide customer rage and brand damage" (a fair and unusually candid point from a vendor).
For context: across our AI resolution-rate benchmark corpus of 195 rated deployments and around 55 vendors, the field median lands near 70%. My AskAI averages about 72% resolution on a rolling basis across our base.
Both sit around the center of the field, because resolution numbers aren't apples to apples between vendors: each vendor defines its own numerator, and the rate depends heavily on your ticket mix and how much knowledge you've connected. For what it's worth, we count a conversation resolved when the AI handled it without escalating to a human, and we keep escalation deliberately easy, so you know exactly what the number does and doesn't tell you.
Which AI agent is easier to improve over time: Decagon or My AskAI?
TL;DR: Decagon wins this one. It ships best-in-class governance tooling: Git-style Agent Versioning with staging and production workspaces, Watchtower always-on QA, live A/B experiments, and Knowledge Suggestions that auto-draft KB articles monthly. My AskAI's self-learning loop improves automatically from agent edits with far less setup, but it's lighter-touch than Decagon's CI/CD-grade tooling.
I'll give this category to Decagon, because the tooling depth is real.
Agent Versioning treats every AOP, tool and guideline edit as a versioned commit, with isolated production and staging workspaces, diff review, one-click rollback, audit logs, branch protections and release gates. If you've ever shipped software, it reads like Git for your support agent, and for a large team where a bad change could hit hundreds of thousands of conversations, that governance pays for itself. On top of it, Watchtower runs always-on QA reviewing every conversation against custom rubrics, Experiments let you A/B test agent versions live, Simulations replay historical transcripts to catch regressions, and Knowledge Suggestions analyzes conversations where customers didn't get a complete answer and auto-drafts new KB articles monthly for a human to publish.
My AskAI improves in a lighter, more hands-off way. Our Self-Learning drafts new knowledge automatically by comparing the AI's reply to the human agent's actual reply on handed-over tickets, so the knowledge base tops itself up without a tuning cycle.
You can train on historic tickets, simulate against your own past tickets before launch, and Insights scores 100% of conversations for AI CSAT (not the usual small sample). And when you want to know why the agent did something, you can ask Echo why it gave any answer and which source it used.
Ours is lighter and needs no engineering; Decagon's is deeper, CI/CD-grade and heavier. If you've got the team to run the heavier tooling, Decagon gives you more control.
Which has more features, Decagon or My AskAI?
TL;DR: Decagon has the broader feature set today, including voice, outbound voice, SMS, AI Actions, Watchtower QA, Trace View observability, Ask AI reporting and Duet. My AskAI includes the support-specific features most mid-market teams actually use, self-serve, without a rollout project.
If you're counting features on a slide, Decagon wins. The list isn't even.
Decagon's platform spans voice and outbound voice, SMS, AI Actions (refunds, order updates, identity verification across Stripe, Shopify and Salesforce), Watchtower QA, Trace View observability (trace every AI decision down to which model, which workflow and which KB article it used), Ask AI natural-language reporting, and the Spring 2026 additions of Duet, Agent Workbench and Proactive Agents. It's a deep, wide product built for enterprises that want one platform doing everything.
My AskAI covers the support-specific features most teams reach for, and lets you turn them on yourself: direct and internal-note replies, Tasks and Tools for agentic workflows like refunds and cancellations (which can run fully autonomously or as propose-then-approve, your call per action), Guidance, Multibrand, live agent translation, Image Reading, Spam Filters, Custom Domains for white-labeling, and AI Tagging on Zendesk, Intercom, Freshdesk and Freshchat.
Here's the grid:
Feature | My AskAI | Decagon |
Direct replies | ✅ | ✅ |
Copilot | ✅ | ✅ (Zendesk only) |
Internal-note mode | ✅ | — |
Voice / phone | — | ✅ |
Outbound voice | — | ✅ |
SMS | — | ✅ |
AI Actions (refunds, order updates) | ✅ Via Tasks/Tools | ✅ |
Past-ticket training | ✅ | ✅ |
Notion / Drive ingestion | ✅ | Not documented |
Historical-ticket simulation | ✅ | ✅ |
Agent translation | ✅ | — |
Always-on QA (Watchtower) | — | ✅ |
Decision observability (Trace View) | — | ✅ |
Decagon leads on breadth, especially voice and observability. We lead on the internal-note on-ramp and self-serve translation, and match on the things mid-market teams use daily.
Is it easy to customize My AskAI and Decagon?
TL;DR: My AskAI gives you self-serve knobs on tone, wording and guidance you can change yourself in minutes. Decagon's AOPs and AOP Copilot are powerful and non-technical to draft, but advanced customization still needs engineering and often routes through your assigned project manager and engineer.
Customization is where the self-serve versus white-glove split shows up again.
With My AskAI you tune behavior yourself through our Guidance: plain-language rules for tone, terminology, specific scenarios and forced-handover cases, plus Custom Answers for wording you want returned verbatim. You can change any of it in minutes, and Echo can even write, edit and merge Guidance rules for you if you'd rather describe the change than build it.
Decagon's AOPs are its customization surface, and its AOP Copilot makes them non-technical to draft, which is a strength. The friction comes at the advanced end: a 2026 third-party comparison notes that Decagon (like Sierra) "still require[s] code execution for AOPs/SDK, prolonging onboarding", and in practice deeper or production-grade changes tend to route through the assigned APM or Forward-Deployed Engineer. So the initial authoring is easy; the deeper the change, the more Decagon's team handles it for you.
What about vendor lock-in?
TL;DR: My AskAI runs inside whichever of the five helpdesks you already use (Zendesk, Intercom, HubSpot, Freshdesk, Gorgias) and the trained agent moves across if you switch. Decagon is a standalone platform that sits above a separate helpdesk you still need for human handoff, so it's a second system to rip out if you leave, and its copilot works only if that helpdesk is Zendesk.
Think about lock-in before you sign.
My AskAI lives inside the helpdesk you already run (we don't ask you to move anything), so you keep your agents, macros, tags and routing untouched. If you ever change helpdesk, the trained agent, custom answers, guidance and tasks move across, so switching platforms doesn't mean re-implementing your AI. There's no parallel system to maintain.
Decagon is architecturally the opposite. It's a standalone platform that requires, and sits above, a separate helpdesk or contact center for human handoff (a second system in your stack, on top of the helpdesk you keep paying for), and one you'd have to rip out if you ever moved on.
As one competitor analysis put it, "adopting Decagon means migrating everything." Its Agent Assist copilot also only works if your helpdesk happens to be Zendesk, and because everything connects by direct API with no marketplace listing, there's more wiring to unpick.
This is just the trade-off of adopting a standalone platform instead of a layer inside the tools you already use.
Does Decagon or My AskAI have any other AI features?
TL;DR: Both auto-tag tickets. Decagon adds sentiment and fraud monitoring through Watchtower, voice analytics, and Ask AI natural-language reporting; My AskAI adds live agent translation. Decagon has the broader spread here.
Beyond answering tickets, both agents do a few extra jobs, and the spread again favors Decagon on breadth.
Tagging
Both auto-tag incoming tickets. Our AI Tagging runs on Zendesk, Intercom, Freshdesk and Freshchat, classifying each ticket by the meaning of the incoming message against your existing tag taxonomy, and it doubles as a spend control since you can route a tagged class of tickets straight to a human. Decagon tags too, as part of its wider monitoring stack.
Agent translation
This is a My AskAI feature Decagon doesn't match. Our Live Translation translates a conversation into your agent's language as an inline note on handover, then translates the reply back, and My AskAI auto-detects 95 languages per message across the board. It solves the "I can't read what my customer just wrote" problem on escalation.
Sentiment, QA and fraud monitoring
This is Decagon's breadth edge. Watchtower monitors sentiment across conversations, flags fraud mentions and regulated complaints, and alerts on compliance risk, and Decagon layers voice analytics and Ask AI natural-language reporting on top. For a large, regulated operation, that monitoring surface is a draw.
What about security, is Decagon more secure than My AskAI?
TL;DR: Decagon has the broader compliance grid and the most buyer-verifiable trust center in the category. My AskAI is SOC 2 Type II and GDPR compliant, which clears the bar for most B2B SaaS and ecommerce. If you need HIPAA, PCI or ISO 27001, Decagon has them and My AskAI doesn't.
Your security reviewer will care about this section.
On security, Decagon is the one to beat: it runs the deepest and most verifiable trust setup in the AI customer-service category. Its trust center (on Vanta) lets buyers download SOC 2 Type II reports plus a bridge letter, and lists ISO 27001:2022 (certified January 2026), HIPAA with BAAs on enterprise, PCI DSS 4.0.1, EU AI Act alignment, and GDPR and CCPA.
It encrypts with AES-256 at rest and TLS 1.2+ in transit, auto-redacts PII with Google DLP, holds zero-day retention with its LLM providers, and supports SSO. The one fair caveat is that G2 reviewers note user roles are still fairly basic and audit logs could go deeper, but the certification grid itself is category-leading.
My AskAI is SOC 2 Type II and GDPR compliant, with AES-256 encryption at rest, TLS in transit, isolated containers per customer, and a firm rule we hold to: your data is never used to train models or for anything beyond serving your own tickets. For most B2B SaaS and ecommerce teams, that's exactly the grid their security review is looking for.
Where the two differ is the extra certifications, so here it is as a straight comparison:
Certification | My AskAI | Decagon |
SOC 2 Type II | ✅ | ✅ |
GDPR | ✅ | ✅ |
ISO 27001 | — | ✅ |
HIPAA | — | ✅ |
PCI DSS | — | ✅ |
If your industry requires HIPAA, PCI or ISO 27001 on paper, Decagon carries them and we don't, and that's a legitimate reason to choose it. If your requirement is SOC 2 Type II and GDPR, both clear it.
Which costs more, Decagon or My AskAI?
TL;DR: My AskAI publishes $0.10 a ticket you can read and start today, with a 30-day trial. Decagon publishes no price at all, requires a sales call, and bills a usage-based conversation or per-resolution contract; third-party data puts its median deal around $433,000 a year, with no trial to measure your volume first.
This is usually the section that decides it, and the two couldn't be further apart.
The pricing model
My AskAI is per-ticket and published on the page: roughly $0.10 a ticket (every two AI replies is one credit; email tickets are about $0.15). Plans are Pro at $199/mo, Scale at $499/mo, and Enterprise from $999/mo, and because it's priced per ticket, your bill stays flat as the AI gets better while a per-resolution model climbs as resolution rises. You also get that 30-day free trial, all features, unlimited tickets, no card, so you can test everything and measure your real volume before you commit a cent.
Decagon publishes no price at all. Its pricing page shows a sales-consultation form and no number, and it runs two usage-based models: per-conversation (a fixed rate per incoming conversation regardless of outcome, which Decagon says most of its customers gravitate to) or per-resolution (a higher rate charged only when a conversation is fully resolved). There are no per-seat fees, but there's also no free trial and no self-serve way to see what your volume would cost.
The overall cost
Because Decagon won't quote publicly, the real figures come from third parties. Vendr's contract data puts the median annual deal around $432,750, with a range of roughly $105,000 to $923,000, and discounts appearing for very large volumes.
Sacra estimates roughly $1.50 per resolution. I'd treat both as third-party estimates, since Decagon publishes no rate of its own, and I'd resist any table that models Decagon as a neat "floor plus rate per conversation", because Decagon never published one and doing the math additively overstates it.
At typical mid-market volume, say 10,000 tickets a month, Decagon likely won't sell to you at all, because you're well below the enterprise-scale volumes it qualifies for (reported to run up into the hundreds of thousands of conversations a year).
My AskAI at that volume on Scale, with 75% resolution, works out to about $1,299 a month, and stays flat as resolution climbs. Structurally, Decagon's price is unknowable until you're deep in a sales process, its unit is negotiated, and there's no trial to measure your real volume first, whereas ours is on the page and you can trial it against your own tickets.
These are different kinds of purchase: My AskAI is the AI layer inside the helpdesk you keep paying for, while Decagon is a standalone second platform.
RecruitCRM evaluated and rejected Intercom Fin specifically over its per-resolution pricing before choosing My AskAI, precisely because a rate that grows as the AI improves is hard to forecast. Decagon's per-resolution option works the same way, with the added wrinkle that you can't measure your day-one rate before signing.
Conclusion - should I choose Decagon or My AskAI?
TL;DR: My AskAI wins overall for mid-market teams that want transparent pricing, fast self-serve setup and helpdesk-native deployment. Decagon wins for enterprises with huge volumes that need voice, omnichannel, the deepest governance tooling and the broadest compliance grid.
If you're a mid-market team that wants to be live this week on the helpdesk you already run, at a price you can read off the page, My AskAI is the better pick, and the one thing that flips it is scale-plus-voice: if you're routing hundreds of thousands of conversations a year and need phone support, Decagon is built for exactly that and earns what it charges.
Let's summarize the categories:
My AskAI | Decagon | ||
Modes | 8/10 | 8/10 | Tie |
Ease of setup | 9/10 | 5/10 | My AskAI |
Training/Integrations | 8/10 | 7/10 | My AskAI |
Answer Quality | 8/10 | 8/10 | Tie |
Improving | 7/10 | 9/10 | Decagon |
Features | 7/10 | 9/10 | Decagon |
Price | 9/10 | 3/10 | My AskAI |
Customization | 8/10 | 7/10 | My AskAI |
Lock-in | 8/10 | 5/10 | My AskAI |
Other AI features | 7/10 | 8/10 | Decagon |
Security | 7/10 | 9/10 | Decagon |
Add it up and My AskAI comes out ahead overall, 86 out of 110 to Decagon's 78.
Decagon takes four categories outright (Improving, Features, Other AI features and Security) and ties two more, because its feature breadth, governance tooling and compliance grid are well ahead. My AskAI wins the other five on the strength of setup, price, lock-in, customization and the modern-knowledge integrations, which is where mid-market buying decisions usually turn.
It's close where the products overlap and lopsided where their markets diverge.
For the record, "built for scale" isn't Decagon's alone: one anonymized My AskAI deployment handles around 105,000 tickets a month at 73% resolution on Intercom, per our high-volume case study, so real volume isn't a reason to rule us out.
Choose Decagon if:
- You handle hundreds of thousands of conversations a year and are past its qualification bar.
- You need voice or outbound-voice AI, or SMS and omnichannel.
- You require HIPAA, PCI or ISO 27001 compliance on paper.
- You want the deepest governance and versioning tooling (Agent Versioning, Watchtower) and a managed, professional-services-led rollout, and you're price-insensitive and already on Zendesk or Salesforce.
Otherwise, choose My AskAI: transparent per-ticket pricing you can read and start today, live in days inside your existing helpdesk (including Freshdesk, which Decagon doesn't support), native Notion, Drive and Confluence ingestion, a real 30-day trial with historical-ticket simulation, and support that comes straight from the founders.
And if Decagon isn't quite your fit but you like where it sits, our Decagon alternatives roundup is worth a read, and if you want another head-to-head with a sales-gated AI agent, see how My AskAI compares to Brainfish.
FAQs
Can My AskAI fully replace Decagon for AI customer support?
For tier-1 support inside your helpdesk, yes: My AskAI does the same core job of resolving repetitive tickets and handing off cleanly to a human. What it doesn't replace is voice and contact-center routing, or the omnichannel breadth Decagon runs at enterprise scale. If your requirements are chat, messaging and email support with agentic actions, we've got you covered; if they include phone and SMS at enterprise volume, Decagon does things we don't.
What can My AskAI and Decagon each be trained on?
Both connect help centers, structured knowledge and past tickets. The difference is at the edges: we add self-serve Notion, Google Drive, SharePoint and Confluence upload plus bulk historical-ticket simulation, while Decagon is stronger on Salesforce CRM records and Shopify/Stripe.
Source | My AskAI | Decagon |
Help center / KB | ✅ | ✅ |
Past tickets | ✅ | ✅ |
Notion / Drive / SharePoint | ✅ | Not documented |
Salesforce CRM records | Knowledge pages | ✅ |
Shopify / Stripe | ✅ (Shopify) | ✅ |
Internal-only marking | ✅ | Not documented |
How long does setup take and do we need developers?
My AskAI is self-serve: about 10 to 15 minutes to connect knowledge and install the app (no developer needed for a standard setup), and most teams fully switch inside a day. Decagon is a sales-led, white-glove rollout of roughly six weeks with a dedicated project manager and forward-deployed engineer, and there's no self-serve signup or free trial to try it first.
How do My AskAI vs Decagon pricing models differ, and what might we actually pay?
My AskAI is per ticket at about $0.10 (published right on the page), with a 30-day free trial. Decagon publishes no price, requires a sales call, and bills per conversation or per resolution; third-party data puts its median deal around $432,750 a year.
My AskAI | Decagon | |
Pricing model | Per ticket (flat) | Per conversation or per resolution |
Headline rate | ~$0.10 / ticket | No public rate |
Worked example | ~$1,299/mo at 10k tickets, 75% resolution (Scale) | ~$432,750/yr Vendr median; ~$1.50/resolution (Sacra estimate) |
Free trial | 30 days, all features, no card | None |
Can they handle multilingual support and agent translations?
Both handle multilingual support. We auto-detect 95 languages per message and add Live Translation so agents can read and reply to conversations in a language they don't speak. Decagon supports customer conversations in any language too, with 15 confirmed in one published deployment.
How do My AskAI and Decagon compare on security and compliance?
Decagon has the broader grid: SOC 2 Type II, ISO 27001:2022, HIPAA, PCI DSS 4.0.1, EU AI Act and GDPR, all verifiable through its trust center. We're SOC 2 Type II and GDPR compliant, which is enough for most B2B SaaS and ecommerce teams. If you specifically need HIPAA, PCI or ISO 27001, that's a point for Decagon.
Will I be locked in to one helpdesk?
With My AskAI, no: it runs inside whichever of the five helpdesks you use (Zendesk, Intercom, HubSpot, Freshdesk, Gorgias) and the trained agent moves across if you switch. Decagon is a standalone platform that needs a separate helpdesk for human handoff, doesn't connect to Freshdesk, and limits its copilot to Zendesk, so it stays a second system in your stack that you maintain separately.
Does each one offer a free trial?
We do: 30 days, every feature unlocked, unlimited tickets, no credit card, and you can simulate against your own past tickets before going live. Decagon doesn't offer a free trial; the only way in is a sales demo.
