Sierra vs Cresta: An honest look at enterprise AI in 2026

Kurnia Kharisma Agung Samiadjie
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Kurnia Kharisma Agung Samiadjie

Katelin Teen
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Katelin Teen

Last edited September 2, 2026

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Sierra vs Cresta: An honest look at enterprise AI in 2026

Disclosure: This article is published by eesel AI, a competitor of Sierra and Cresta. We encourage you to read Sierra's own materials and Cresta's own materials for their perspective.

Conversational AI for enterprise contact centers has two names that come up in almost every serious evaluation: Sierra and Cresta. Both are well-funded, both target large organizations, and both promise to change how companies handle customer interactions. But they start from different premises, and that shapes everything: what the product actually does, how it gets deployed, and what it costs.

This guide compares Sierra vs Cresta on the dimensions that matter most. We cover what each platform is built to do, how pricing works, what implementation looks like in practice, and when you'd choose one over the other.

What is Sierra?

Sierra is an Agent Operating System for enterprise customer experience. Founded in late 2023 by Bret Taylor (former co-CEO of Salesforce and current chair of OpenAI's board) and Clay Bavor (18-year Google veteran), the company reached $150M ARR by February 2026 and closed a $950M round at $15.8B in May 2026. More than 40% of the Fortune 50 are Sierra customers, per TechCrunch.

The core product is a fully autonomous AI agent for customer-facing interactions. Sierra agents connect to back-end systems through the Agent SDK, which supports API-based integrations with CRMs, order management systems, and other records, allowing them to take real actions, such as processing a return or updating a subscription, rather than just answering questions. For non-technical teams, Agent Studio provides a no-code workflow builder, a GitHub-style collaboration environment, and a pre-built integration library. The Agent Data Platform, launched in November 2025, adds persistent memory so agents retain context across conversations. Ghostwriter, launched in March 2026, builds production-ready agents from standard operating procedures, call transcripts, or plain English descriptions.

Sierra's Agent Studio, the no-code environment for building and managing agents, as taken from Sierra
Sierra's Agent Studio, the no-code environment for building and managing agents, as taken from Sierra

Sierra's published customer results include Ramp at 90% case resolution, Chime at 70%+, and AG1 at 99% of interactions scoring 5/5 on customer satisfaction. Agents deploy across chat, voice, SMS, WhatsApp, email, and now ChatGPT from a single configuration.

What is Cresta?

Cresta calls itself the "only unified platform" for human and AI agents built for enterprise scale. Founded in 2017 at Stanford's AI Lab and now above $100M ARR, Cresta is backed by a16z, Sequoia, Greylock, and Tiger Global. Its G2 reviewer base is 87% enterprise, with named customers including United Airlines, Cox Communications, Marriott, Hilton, Intuit, and Brinks Home.

Unlike Sierra's full-automation focus, Cresta runs two tracks in parallel: autonomous agents for volume, and real-time coaching tools for human agents.

On the automation side, Cresta AI Agent handles voice, chat, and SMS in 30+ languages, with API and MCP-based function calling for CRM and backend systems. Snap Finance reports 5.5x containment lift and 23% higher CSAT; Xanterra reached a 74% containment rate with $3.3M in revenue lift.

On the human side, Agent Assist delivers real-time behavioral hints, proactive knowledge surfacing, and AI-generated summaries mid-conversation. Crissa Warner-Graham, Director of Marketing at Holiday Inn Club Vacations, described the coaching impact as "100% better because it's instant" (Agent Assist).

Cresta Agent Assist, its real-time coaching layer for human agents, as taken from Cresta
Cresta Agent Assist, its real-time coaching layer for human agents, as taken from Cresta

Cresta's Conversation Intelligence suite covers natural-language analytics over call data, Quality Management that auto-scores 100% of conversations (contrasting its own approach explicitly with keyword-based detection), and Cresta Coach, which links agent behaviors to business outcomes for supervisor-led coaching. Cox Communications' Director of Contact Center Training noted that Cresta replaced a process (Conversation Intelligence) that "used to take 6 weeks and more than $100,000" with real-time analysis.

Comparing the two platforms

Core approach

The most important difference in the Sierra vs Cresta comparison is what each platform is optimized for.

Sierra's single metric is resolution rate: how many customer issues the AI resolves without a human ever intervening. The platform is built for teams ready to commit to a fully autonomous AI workforce for their most common support cases.

Cresta is designed for teams that want both. Autonomous agents handle the volume; Agent Assist and Cresta Coach improve how human agents perform on everything else. The two tracks share context and data, so AI Agent handoffs to humans come with full conversation history and summaries already generated.

If your contact center runs a large team of human agents and you need to improve their consistency as much as you want to automate volume, Cresta's model maps to that goal more naturally. If you want to maximize the share of interactions resolved without human involvement, Sierra is built for that.

Pricing

Pricing for both platforms is not publicly disclosed.

Sierra does not publish a pricing page. All contracts are custom-quoted through a sales process. Sierra's stated model is outcome-based: you pay when the agent achieves a defined successful resolution, not per message or per seat.

Cresta also does not publish pricing. The cresta.com/pricing URL returns a 404; every product page leads to a "Get a demo" form. The only publicly visible Cresta price points appear on AWS Marketplace as 12-month listing terms for Agent Assist only: $150,000/year for up to 125,000 chat interactions or 100,000 voice calls, with per-interaction overages. These are AWS Marketplace listing terms for one specific module, not pricing Cresta publishes on its own site. Cresta's own note on the listing directs enterprise buyers to contact them directly for a private offer.

Neither platform lets you model costs before entering a sales cycle.

Implementation

Sierra case studies report go-live timelines of 4 to 10 weeks for customers like Singtel (under 10 weeks) and Vivid Seats (4 weeks). There is no self-serve path; every deployment goes through Sierra's implementation team. G2 reviewers describe the team as responsive and supportive, while also flagging a steep learning curve during initial setup and limited ability to self-edit without involving the vendor.

Cresta describes its deployment as "white glove" with implementation, training, and customer success support included. Cresta's own pages do not publish a specific deployment timeline. One G2 reviewer in a university admissions role (9/18/2025) described the experience: "You have to have patience and really a dedicated person who is almost an AI linguist once you figure it out everything changes but pack patience once you have it down its amazing." (G2)

Quick comparison

FactorSierraCresta
Primary focusAutonomous resolution at scaleAutonomous agents + human-agent coaching
Human coachingLive Assist (launched Nov 2025)Agent Assist (core product)
Quality managementNot a named product100% auto-scored
ChannelsChat, voice, SMS, WhatsApp, email, ChatGPTVoice, chat, SMS in 30+ languages
Self-serve signupNoNo
PricingNot publicly disclosed (sierra.ai)Not publicly disclosed (cresta.com)

Which platform is right for you?

Choose Sierra if your absolute priority is automating as many customer interactions as possible and you have the engineering resources and timeline to support a custom enterprise deployment.

Choose Cresta if you need autonomous agents and human-coaching tools in the same platform, especially in large contact centers where quality management and agent performance analytics matter alongside containment rate.

A faster path to AI support

Both Sierra and Cresta are built for enterprise buyers willing to go through a custom sales and implementation process. If that process does not fit your timeline or budget, there is a different starting point.

eesel AI works as an AI agent layer on top of helpdesks you already use, including Zendesk, Freshdesk, and others. Setup takes under 15 minutes with no sales call required. You can deploy it as a fully autonomous agent that resolves tickets end-to-end, or as an AI copilot that drafts replies for your team to approve. A simulation mode runs the AI against your historical tickets before it touches a live customer, so you can see the projected performance and tune behavior in advance.

Pricing is public: $0.40 per helpdesk task. No long-term contract, no custom quote.

The bottom line

Sierra and Cresta represent two distinct approaches to AI in the contact center. Sierra bets on fully autonomous agents replacing human handling for the highest-volume cases. Cresta bets on a platform that makes every part of the contact center better, both the AI handling and the human agents working alongside it.

Both require a meaningful commitment of time, resources, and budget. Before entering either sales process, it is worth establishing what your current support operation can actually automate, and what resolution rate would justify the investment. Starting with a self-serve platform gives you real data on those questions before you negotiate.

Frequently asked questions

What is the core difference in approach between Sierra and Cresta?

Sierra is built primarily for full autonomous resolution: its agents are designed to handle customer problems end-to-end without human involvement. Cresta runs both autonomous AI agents and real-time human-agent coaching in one platform, so contact centers can automate volume while still improving how human agents perform. The choice comes down to whether you want to replace human involvement in routine cases, augment it, or both.

Is pricing for Sierra or Cresta available online?

Neither Sierra nor Cresta publishes pricing publicly. Both require a sales engagement before you can model costs. If upfront pricing transparency matters, eesel AI publishes its full pricing on its website, with task-based costs starting at $0.40 per helpdesk interaction and no long-term contract required.

Which platform is better suited if coaching human agents is as important as automation?

Cresta. Its Agent Assist product has been a core offering for years, delivering real-time behavioral hints and knowledge answers mid-conversation, and its Quality Management module auto-scores every interaction. Sierra's human-assist product, Live Assist, was announced in November 2025 and is newer to the market. For large contact centers where agent performance matters as much as containment rate, Cresta has the deeper product history in that area.

Are there alternatives that work for teams that need to move faster than an enterprise deployment allows?

Yes. eesel AI connects to helpdesks like Zendesk and Freshdesk in under 15 minutes, with no dedicated implementation team required. It supports both a fully autonomous agent and an AI copilot mode so teams can start with human oversight and expand as confidence builds.

What should teams verify before committing to either platform?

Before signing, confirm the full cost structure (platform fee, per-outcome or per-interaction rates, and professional services fees), the expected go-live timeline based on your specific integrations, and what ongoing support looks like after implementation. Running a self-serve pilot on a platform like eesel AI can help you establish a resolution-rate baseline and identify which ticket types are genuinely automatable before entering an enterprise negotiation.

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Kurnia Kharisma Agung Samiadjie

Article by

Kurnia Kharisma Agung Samiadjie

Kurnia is a software engineer and writer at eesel AI with two years of SEO experience, writing about AI tools, helpdesk software, and customer support. He pairs a developer's understanding of how these products are built with search-driven research into what actually ranks and resonates with the people searching for them.

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