Ada is one of the more mature customer-service automation platforms shipping in 2026. Founded in Toronto in 2016 by Mike Murchison and David Hariri, it was an early mover in this category, and that head start shows in the depth of its configuration and its focus on automated resolution (Ada, retrieved 2026). Its AI Agent is built to resolve customer-service inquiries automatically across channels and many languages, and Ada positions hard on resolution rate and coverage. For a support organization that wants a dedicated CX product, it is a strong, serious pick.
This piece walks through what Ada is in 2026, what Gravity does differently, and the moments where one wins decisively over the other. The honest framing up front: these are two different categories. Ada is a focused customer-service resolution platform. Gravity is a general operator platform that runs expert-built agents across many tasks. Picking the wrong one for your problem is the expensive mistake, so this stays specific and fair.
What Ada is, and where it actually shines
Ada is an automated customer-service platform. Its product centers on an AI Agent that resolves inbound support inquiries without a human in the loop wherever the answer can be handled safely, and routes the rest. You configure it on your own content: you connect a knowledge base, encode your policies, and connect the systems the agent needs to take action, such as order lookups or account changes (Ada, retrieved 2026). Once configured, it answers across channels and many languages, which is a real strength for global support teams.
Automated resolution as the core metric
Ada built its positioning around automated resolution rate, the share of inquiries the agent closes on its own. That focus matters because it is the metric support leaders actually buy on. A platform that resolves a meaningful fraction of contacts without a human reduces queue load and cost per contact directly. Ada has spent years tuning toward that number, and a buyer evaluating CX automation should ask for it against their own contact mix.
Channel and language coverage
One of Ada's clearest strengths is breadth of coverage inside the support lane. It is built to work across email, chat, and messaging surfaces, and to answer in many languages, so a single deployment can serve a global customer base. For a support organization whose customers write in dozens of languages across several channels, that coverage is a meaningful advantage over a narrower point tool.
Where Ada is excellent
Three places where Ada is the clear pick. A mid-market or enterprise support team whose primary goal is lifting automated resolution rate. A global operation that needs consistent answers across channels and languages. And any team that already has the support content, policies, and ownership to configure a dedicated platform deeply and keep it current. For how Ada fits the wider field, see our roundup of the best AI agents in 2026 and our guide to enterprise AI agent platforms.
What Gravity does differently
Gravity is not a customer-service product; it is a general agent platform. You describe the outcome you want in plain language, and Gravity matches you with an expert-built agent that runs it in about 60 seconds. There is no platform to configure on your knowledge base before you get value, and the scope is not limited to support. The same platform can triage tickets, draft a report, monitor a queue, enrich a record, or handle a task in finance or operations, because the unit of work is an agent an expert already built and tested, not a deployment you stand up. You pay per use, $1 buys 1,000 credits, with no subscription required. For the shape of the platform, see how Gravity works.
The trade-off is honest. Because Gravity is broad rather than CX-specific, it does not give a support team the depth of a dedicated resolution platform: the years of tuning toward automated resolution rate, the support-specific reporting, and the deep configuration surface that Ada offers. If customer service is your single hardest problem and you want a product built only for that, a focused platform will go deeper than a general one. Gravity trades that depth in one lane for reach across many.
How the platform is structured
Gravity is the platform that runs the agents. Users describe an outcome and pay per use, and Gravity carries the execution cost and the platform overhead. Expert builders build and maintain agents for Gravity, and Gravity pays them for that work, runs the agents, and owns reliability. That structure is the difference from a configure-it-yourself platform: with Ada your team configures and owns the deployment, while on Gravity an expert builds and maintains the agent and the platform runs it for you. For how to weigh products like these, see how to evaluate AI agent platforms.
Side-by-side comparison
The honest comparison runs along ten dimensions. Below is how the two products stack up as of 2026. Where a current Ada number is uncertain, that is flagged rather than invented.
| Dimension | Ada | Gravity |
|---|---|---|
| Category | Dedicated customer-service automation platform | General agent platform across many tasks |
| Pricing model | Custom enterprise pricing, contract-based | Pay per use, $1 = 1,000 credits, no subscription |
| Setup time | Configure on your knowledge base and policies, days to weeks | Describe the outcome, run in about 60 seconds |
| Who builds the agents | Your team configures Ada's AI Agent | Vetted expert builders |
| Who maintains it | Your support team, ongoing | Expert builders, paid by Gravity to maintain for the platform |
| Core strength | Automated resolution rate across channels and languages | Breadth of tasks and time-to-result |
| Channels | Email, chat, and messaging support surfaces | Runs tasks across functions, not channel-bound |
| Target user | Mid-market and enterprise support organizations | Non-technical operators who want outcomes |
| Hosting / data residency | Ada-operated cloud | Operated by XAI Technologies Pvt Ltd |
| Commitment | Enterprise contract and onboarding | Pay-per-run, no seat contracts |
A few rows favour Ada outright. For customer service specifically, the depth of configuration, the focus on resolution rate, and the channel and language coverage are genuinely strong, and a general platform will not match them in that lane. A few favour Gravity: time-to-result, breadth across tasks, and pay-per-use economics with no contract. Several rows are buyer-dependent. Weight them by what your work looks like, not by which product sounds more capable on paper.
Configure a platform vs run an expert's agent
The deepest difference between Ada and Gravity is not a feature; it is how much you own. Ada is a platform you configure and run. The promise is a high automated resolution rate on your support volume, and reaching it is a real project: you connect the knowledge base, encode policies, wire the systems the agent acts through, test it against your contact mix, and keep it current as products and policies change. That ownership is the cost of the depth. For a team whose core problem is support, it is a cost worth paying, and the same reliability discipline applies, which is why reliability testing matters before any agent touches live customers.
Gravity removes the configuration project. Someone with deep expertise built the agent, tested it across scenarios, and brought it to the platform so you can run it. The mental model is closer to hiring than to deploying. This is the build-versus-buy distinction we draw in build vs buy AI agent: configuring a dedicated platform gives you control and depth and costs you time and ownership, while running a finished agent gives you speed and breadth and costs you some of that depth. Ada is the strong expression of own-the-deployment in CX. Gravity is a bet on run-the-outcome across many tasks.
There is also a category point worth being precise about. Ada is built to be the frontline that resolves customer contacts; that is a deliberately narrow, deep job. A Gravity agent is built to take an outcome and execute it end to end across whatever the task is. The words bot, assistant, and agent get abused in marketing, so if the distinction matters to your purchase, see AI agent vs chatbot vs assistant for the clean version.
Ownership, hosting, and pricing reality
Ada is a Toronto-headquartered company and operates its platform as enterprise software, with custom pricing rather than a public per-use rate. You request a quote, scope a deployment, and contract for it, which is normal for a product sold to mid-market and enterprise support organizations. The fair framing is procurement, not criticism: if your organization has GDPR, SOC 2, or sector-specific requirements, review Ada's hosting and data-residency posture with your security team, the same diligence any vendor deserves. Verify current commercial and data-residency terms with Ada directly before you budget.
Gravity is operated by XAI Technologies Pvt Ltd, based in Bangalore, and is in pre-launch waitlist as of 2026. The model is pay per use rather than per seat: $1 buys 1,000 credits and you spend them only on runs you actually use, with no subscription required. As a pre-launch product, its data-residency posture at general availability is still being finalized, so this piece does not overclaim it. For the broader economics of paying for agents, see build vs buy AI agent, and for how Gravity compares to other autonomous-agent products, our Gravity vs Lindy and Gravity vs Manus breakdowns go deeper.
When Ada is the right choice
Three signals say Ada is the better purchase. First, customer service is your core problem and lifting automated resolution rate is the goal you are buying against. Second, you operate across channels and languages and need consistent, configured answers everywhere your customers reach you. Third, you have the support content, policies, and team to configure a dedicated platform deeply and keep it current. If those three are true, a focused CX product will go deeper than a general one, and Ada is a serious option. For where it sits among peers, see enterprise AI agent platforms, and pair any support deployment with sound guardrails before it goes live.
When Gravity is the right choice
Three opposite signals say Gravity is the better purchase. First, your work spans many tasks, and a CX-only platform would solve one slice while leaving the rest. Second, you want an outcome rather than a deployment to configure and own; you would rather type what you need and get a result than stand up and tune a platform. Third, pay-per-use economics fit your usage better than an enterprise contract, especially if volume is uneven. If you do still want help on the support side specifically, narrower task agents like an agent for Zendesk ticket triage or an Intercom auto-responder can cover focused jobs without an enterprise commitment. For more on the platform approach, see about Gravity.
Using both together
These two products are not strictly either-or. A support organization can run Ada as its dedicated frontline resolution layer, where its depth pays off, while using Gravity agents for the work around support and in other functions: drafting reports, monitoring queues, enriching records, and handling tasks finance or operations need. Ada owns deep CX resolution; Gravity covers the broader operator work that sits next to it. Use the focused tool where focus wins, and the general platform for everything else.
Frequently asked questions
What is the main difference between Ada and Gravity?
Ada is a dedicated customer-service automation platform. You configure it on your knowledge base and policies, and its AI agent resolves support inquiries across channels and many languages. Gravity is a general agent platform: you describe an outcome and run an expert-built agent for many kinds of work, not only support. Ada is purpose-built for CX resolution; Gravity is a broad operator platform.
Is Ada a chatbot or an AI agent?
Ada started in the support automation category and now positions its product as an AI Agent that automatically resolves customer-service inquiries across channels rather than a scripted chatbot. It is built to answer from your knowledge base, follow your policies, and act through connected systems. The line between a bot and an agent is fuzzy in marketing, so judge it on resolution behavior, not the label.
How much does Ada cost compared to Gravity?
Ada sells to mid-market and enterprise support organizations and uses custom enterprise pricing rather than a public per-use rate, so you request a quote and contract for it. Gravity is in pre-launch waitlist as of 2026 and is pay per use: one dollar buys 1,000 credits, with no subscription required. Verify Ada's current commercial terms with their sales team before you budget.
When is Ada the right choice?
Ada is the right choice when customer service is your core problem, when you want a dedicated CX platform that resolves inquiries across email, chat, and messaging in many languages, and when you have the support content and team to configure it deeply. For a support organization that wants a mature, focused automated-resolution product, Ada is a serious pick.
When is Gravity the right choice?
Gravity is the right choice when your work spans many tasks beyond support, when you want an outcome rather than a platform to configure, when you would rather run an expert's tested agent than own and tune a deployment, and when pay-per-use economics fit better than an enterprise contract. It suits operators who value breadth and time-to-result.
Can Ada and Gravity be used together?
Yes. A support team can run Ada as its dedicated frontline resolution layer while using Gravity agents for the work around support: drafting reports, monitoring queues, enriching records, and handling tasks in other functions. Ada owns deep CX resolution; Gravity covers the broader operator work that sits next to it. They serve different jobs and can coexist.
Three takeaways before you close this tab
- Ada and Gravity are different categories. A dedicated CX resolution platform versus a general agent platform across many tasks.
- The fit test is one question. Is your hardest problem support resolution at scale, or a wide range of operator tasks?
- They can be complementary. Run Ada on the frontline, and Gravity for the broader operator work around it.
Sources
- Ada, "Product home", retrieved 2026, ada.cx
- Ada, "AI Agent", retrieved 2026, ada.cx platform
- Gravity, "How it works", gravity.fast
- Gravity team, "How to evaluate AI agent platforms", 2026, how to evaluate AI agent platforms
- Gravity team, "Gravity vs Lindy", 2026, Gravity vs Lindy
- Gravity team, "Gravity vs Manus", 2026, Gravity vs Manus