SentiSum vs Chattermill

Chattermill reports the themes. SentiSum tells your whole organisation what to fix, what it’s worth, and who owns it.

Chattermill is a Voice-of-Customer platform built for insight teams and dashboards. SentiSum is an AI-native intelligence layer built on your own data: it reads every conversation — human or AI — finds the specific failure behind the volume, prices it, routes it to the team that owns it, and shows you the number coming down. Ask it anything in plain language. No dashboard-building required.

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Trusted by high-volume retail, fintech and financial-services brands reading millions of customer conversations a year.

Comparison

SentiSum vs Chattermill, side by side

Compare SentiSum and Chattermill for customer feedback analytics and CX intelligence.

Product comparison

SentiSum

Chattermill

Built for

The whole organisation — Support, Product, Operations, Risk and Leadership read from one layer, and so do your AI agents and copilots

Insight, CX and product-research teams analysing customer feedback

What it analyzes

Every customer conversation in full — calls, chats, tickets, emails, surveys, reviews and your AI bots plus transaction data, read end to end, not sampled

Customer feedback data across surveys, reviews, and social, scored for theme and sentiment

Proactive

An Early Warning agent watches continuously and knows what’s normal for a Tuesday in August. When refunds, login failures or KYC contacts move abnormally, the alert lands in Slack or email while the issue is still small

Anomaly detection and alerting inside the platform, reviewed when someone looks

How you get answers

Ask in plain language, get an evidenced answer in minutes with the source conversations one click away. The report writes itself and arrives in Slack or email

Build and maintain dashboards, then read and interpret them

How deep it goes

Past the bucket to the specific failure inside it — an adaptive taxonomy built from your own data and vocabulary, thousands of drivers, correctable in plain English

Configurable bespoke taxonomy, managed and maintained by your insight team

Extensible

An agentic platform, not a closed tool. Build your own agents on the same layer — agent assist, automated resolution, whatever you need and connect ChatGPT, Claude or Copilot via MCP. Every agent inherits one taxonomy, so your AI investment compounds

MCP access for AI assistants; the platform itself is not a build surface

What you get

The root cause, its dollar cost, the owner of the fix, and proof the number dropped

Themes, sentiment and dashboards to interpret yourself

Why SentiSum

From customer issue to the team that can fix it

Every issue routes to the system or team that created it, not just a dashboard. A report tells you the top themes; it doesn’t make anything change. SentiSum names the cause, the owner and the deadline — then measures whether the number actually fell.

SentiSum closed loop: detect the issue, find the root cause, route it to the owner, and measure the drop

Catch it before it spreads.

A refund spike after a pricing change gets flagged while it’s still small, not after it shows up in the quarterly numbers.

Trace the actual source.

Delivery complaints trace back to the fulfillment centre causing them, not just a rising ticket count with no explanation.

Prove it worked.

Product sees the product friction. Operations sees the fulfillment issue. CX and Support see the quality trend. The fix goes to the owner automatically — and the drop in volume is measured, not assumed.

Why SentiSum

Answers, not dashboards

The most common reason enterprise VoC programmes stall is adoption. The insight team lives in the platform; nobody else opens it.

Anyone can ask.

A plain-language question from anyone in the business returns an evidenced answer in minutes, with the underlying conversations one click away — no analyst queue, no dashboard hunt.

Granular enough to act on.

Not “5,000 customers contacted us about billing” but which billing failure, how many, what it costs, and who owns it.

Correct it in plain English.

Merge, split or exclude anything in the taxonomy by saying so. No model rebuild, no professional-services ticket, no months of custom configuration.

Why SentiSum

One system for human agents and AI agents

Support today runs through a mix of people and bots. SentiSum reads both — and catches the failures that live between them.

The failure no survey and no dashboard can see.

An agent promises a refund or a cancellation on a call. It never gets actioned in the back office. The customer isn’t upset — they were reassured — so nothing flags. Days later they come back, logged as something unrelated, and the real cause stays invisible. SentiSum reads the promise and the follow-up together, so that gap gets found instead of buried.

Grade your own AI agents.

Containment, resolution accuracy and failure points for your bots — not just customer sentiment about them.

Score every conversation, not a sample.

100% of conversations quality-scored, human and AI, on the same layer and the same taxonomy as everything else.

The right fit

Which one’s the better fit

Both are capable platforms. The right choice depends on what your programme is measured on.

Chattermill is the stronger choice

if you’re building a company-wide feedback research capability: deep segmentation, longitudinal dashboards, 100+ languages, and an insight team whose job is slicing the data.

SentiSum is the stronger choice

if you need the organisation to act: the specific failure rather than the theme, what it costs, who fixes it, and proof it worked — delivered to people and to your other AI agents, without anyone living in a dashboard.If your programme is measured on contact reduction, churn, CSAT or cost-to-serve, that’s us.

See what your customer conversations are actually costing you.

Book a 20-minute demo and we’ll show you the fixes hiding in your own conversation data, and the revenue on the other side of them.

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