Sold by: DevRev
Deployed on AWS
Computer, by DevRev, is an AI teammate that connects your business data, understands context, and takes real action across your systems of record. Unlike AI tools that only search or suggest, Computer resolves issues end-to-end. Up to 85% of customer support tickets handled without human intervention. 60% of IT service desk requests resolved automatically. 6+ hours recovered per sales rep per week. Powered by Computer AirSync (patented bidirectional sync with Salesforce, Zendesk, ServiceNow, Jira, Slack, and dozens more) and Computer Memory (AI-native knowledge graph), Computer unifies CRM records, tickets, product backlogs, documents, emails, and conversations into a single AI-ready source of truth. It takes action: updating records, processing requests, routing work, and syncing changes back to your systems. Build and deploy custom AI agents in minutes with Agent Studio. Enterprise ready: SOC 2 Type 2, ISO 27001:2022, GDPR, HIPAA, and CCPA compliant.
4.4
Overview
Computer by DevRev is an enterprise AI platform that connects your business data, reasons with full context, and takes action across your existing systems of record. Unlike generic AI tools that lack business context, Computer operates on a synchronized digital twin of your enterprise - delivering accurate, trustworthy results from day one.
Computer works across five core use cases:
Customer support resolution - Resolves customer inquiries end-to-end across email, chat, Slack, WhatsApp, and more. Handles password resets, subscription changes, and refund processing with built-in guardrails and human-in-the-loop controls. Learns from every human resolution and turns solutions into reusable knowledge. Deploys the same agent across all channels with 24/7 availability and automatic language detection. BILL (FinTech) achieved a 70% AI resolution rate and is on track to save over $6M annually.
Support teams - Helps agents resolve tickets faster by pulling context, checking similar resolutions, and suggesting next steps. Automates triage by analyzing incoming tickets, mapping them to product areas, and auto-assigning type and severity. Proactively scans for negative sentiment and flags at-risk customers. Scores every interaction for tone, grammar, and resolution quality. Phenom (HR Tech) achieved 30% faster mean time to resolution and 29% faster ticket closure.
IT service desk automation - Resolves IT service requests including access provisioning, password resets, software installations, and incident routing. Works alongside ServiceNow, Jira Service Management, and BMC Remedy without requiring replacement. Automates routine L1 and L2 requests. Supports IT, HR, Facilities, and other shared services from a unified platform. Uniphore (Enterprise AI) migrated 16K tickets and 72K comments in approximately 6 hours with Jira and Rocketlane unified in DevRev.
Sales teams - Prepares meeting briefs, generates pipeline summaries, and automates CRM updates. Surfaces account context, open issues, and engagement history to inform deal strategy. Connects support signals to revenue outcomes - flagging at-risk accounts and identifying upsell opportunities.
Operations teams - Tracks progress across projects, teams, and milestones. Identifies risks and blockers before they escalate. Surfaces real-time status updates from connected systems so leaders can act with clarity instead of chasing updates across tools. Pebl (Global Operations) transformed operations workflows, enabling data and work to flow seamlessly across their operational support team.
All five use cases are powered by the same foundational technology:
Computer AirSync is a patented, permission-aware bidirectional sync engine connecting your entire stack - Salesforce, Zendesk, ServiceNow, Google Workspace, Jira, Confluence, Slack, and dozens more. Data stays current, accurate, and accessible from one place.
Computer Memory is an AI-native knowledge graph that organizes every ticket, conversation, and document around your products and customers. It connects issues, resolutions, and outcomes to context that AI can understand, reason with, and act on.
Agent Studio lets you build, test, and deploy AI agents with full observability. Sessions, traces, and built-in evaluations let you measure performance, fix failures, and iterate based on data. No black boxes.
Enterprise-ready from day one: SOC 2 Type 2, ISO 27001:2022, GDPR, HIPAA, and CCPA compliant. Audit trails, flexible data residency, role-based access control, and enterprise SSO. Permission-aware data access at the object level ensures AI respects your existing security boundaries. Human-in-the-loop controls for sensitive operations. Penetration tested and vulnerability assessed.
Highlights
- Trusted by BILL, Phenom, Uniphore, Bolt, Bajaj Finserv, ICICI Prudential, Velocity Global, and Skedulo across FinTech, HR Tech, Enterprise AI, E-commerce, Insurance, and Financial Services, spanning the Americas, Europe, and Asia-Pacific.
- In benchmarks on the same enterprise query, one AI system used 3.2M tokens and took 9 minutes. Computer solved it in 96 seconds using 157K tokens. The patented knowledge graph pays discovery costs once and amortises them across every user and query.
- Computer works with any AI model (Anthropic, OpenAI, Google, or open-source). Swap, mix, or upgrade models without rebuilding. The patented knowledge graph and AirSync keep your enterprise context intact regardless of which model does the reasoning.
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Deployed on AWS
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Dimension | Cost/unit |
|---|---|
DevRev Unit (1 unit) | $0.01 |
DevRev Parts Manager | $0.01 |
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Customer reviews
Ujjwal K.
Dev Rev: Feature-Rich and a Pleasure to Work With
Reviewed on May 07, 2026
Review provided by G2
What do you like best about the product?
Dev Rev have multiple feature and nice to work
What do you dislike about the product?
All is fine and there were nothing anything regarding dislike
What problems is the product solving and how is that benefiting you?
Easier to work
Food & Beverages
Powerful Customer Cohorting and Behavior Filters for Deeper Insights
Reviewed on May 06, 2026
Review provided by G2
What do you like best about the product?
Customer cohorting - The ability to put in specific types of filters of customer behaviour which we can then use to view the recordings
What do you dislike about the product?
As a beginner, it is difficult to navigate.
What problems is the product solving and how is that benefiting you?
It is extremely helpful in identifying edge cases which are causing errors which are nearly impossible to find through data alone
Tushar M.
Powerful Traceability, Though Weighed Down by Complex Onboarding
Reviewed on May 05, 2026
Review provided by G2
What do you like best about the product?
In product management, the biggest bottleneck isn't usually a lack of ideas, but a lack of cross-functional alignment. DevRev's standout value is how it actively breaks down the traditional silos separating support, product, and engineering. Instead of spending hours stitching together context across disparate tools, DevRev creates a unified environment where customer conversations, support tickets, and product signals are natively linked. This shared reality significantly reduces engineering turnaround times and prevents the strategic drift that often happens when teams operate in isolation.
From a tactical standpoint, the platform's traceability is exceptional. When managing complex roadmaps, being able to track a granular customer pain point all the way through to an executed feature or architectural fix makes sprint prioritization far more grounded. It shifts the conversation from subjective opinions to data driven customer impact. Many legacy platforms promise this level of end-to-end visibility, but DevRev is one of the few that actually executes it effectively at the data-model level.
However, implementing this level of structural shift comes with real friction. This is absolutely not a plug-and-play solution; initial onboarding requires serious effort. For teams migrating from traditional, linear ticketing systems, DevRev’s workflow and data model take time to internalize. While the UI is clean, it isn't always intuitive, and building out complex, real-world custom integrations often requires frustrating workarounds. Furthermore, their AI capabilities lack the reliability needed for daily use, and performance can take a noticeable hit when querying heavily linked, large-scale datasets.
Ultimately, DevRev is a highly potent platform that demands a corresponding investment in setup and change management. The ROI curve is positive, but you have to be willing to do the heavy lifting upfront. If your organization is struggling to tie customer feedback directly to engineering execution and you are willing to push through the initial adoption hurdles, the platform delivers tangible value. It is an investment in process maturity rather than just a simple software purchase.
From a tactical standpoint, the platform's traceability is exceptional. When managing complex roadmaps, being able to track a granular customer pain point all the way through to an executed feature or architectural fix makes sprint prioritization far more grounded. It shifts the conversation from subjective opinions to data driven customer impact. Many legacy platforms promise this level of end-to-end visibility, but DevRev is one of the few that actually executes it effectively at the data-model level.
However, implementing this level of structural shift comes with real friction. This is absolutely not a plug-and-play solution; initial onboarding requires serious effort. For teams migrating from traditional, linear ticketing systems, DevRev’s workflow and data model take time to internalize. While the UI is clean, it isn't always intuitive, and building out complex, real-world custom integrations often requires frustrating workarounds. Furthermore, their AI capabilities lack the reliability needed for daily use, and performance can take a noticeable hit when querying heavily linked, large-scale datasets.
Ultimately, DevRev is a highly potent platform that demands a corresponding investment in setup and change management. The ROI curve is positive, but you have to be willing to do the heavy lifting upfront. If your organization is struggling to tie customer feedback directly to engineering execution and you are willing to push through the initial adoption hurdles, the platform delivers tangible value. It is an investment in process maturity rather than just a simple software purchase.
What do you dislike about the product?
The primary drawback is the steep adoption curve; this is definitely not a plug-and-play solution. For teams migrating from legacy ticketing systems, DevRev’s underlying data model requires a significant paradigm shift, and the UI can feel unintuitive during the initial onboarding phase. From a technical standpoint, certain areas still need maturity. Complex custom integrations frequently require frustrating workarounds rather than native support. Additionally, performance can lag noticeably when querying large-scale, heavily linked datasets, and the platform's AI features currently lack the stability required to be useful in daily operations.
What problems is the product solving and how is that benefiting you?
Operating in the enterprise fintech space, specifically managing complex LOS journeys, our biggest operational bottleneck was the disconnect between customer-facing support and engineering execution. Tracking the product impact of major structural shifts such as migrating from a monolithic to a microservices architecture used to be highly fragmented across disparate tools.
DevRev solves this by creating a unified thread from initial customer friction straight to the engineering sprint. For example, when we recently had to mandate a change in our system architecture to support multiple document identifiers per KYC type (shifting from a restricted 1:1 to a 1:M relationship), DevRev allowed us to seamlessly link the upstream compliance requirements and customer requests directly to the active development tickets.
The primary benefit is drastically improved cross-functional alignment. It has significantly reduced our engineering turnaround time on critical updates and ensures our roadmap prioritization is anchored in traceable, real-world user impact rather than siloed assumptions.
DevRev solves this by creating a unified thread from initial customer friction straight to the engineering sprint. For example, when we recently had to mandate a change in our system architecture to support multiple document identifiers per KYC type (shifting from a restricted 1:1 to a 1:M relationship), DevRev allowed us to seamlessly link the upstream compliance requirements and customer requests directly to the active development tickets.
The primary benefit is drastically improved cross-functional alignment. It has significantly reduced our engineering turnaround time on critical updates and ensures our roadmap prioritization is anchored in traceable, real-world user impact rather than siloed assumptions.
Shaik J.
Strong Automation Enhances Customer Management
Reviewed on May 05, 2026
Review provided by G2
What do you like best about the product?
I like DevRev's strong automation capabilities without being rigid, which allows us to set up rules to auto-route cases like payment failures or profile issues. The unified customer context is incredibly valuable because one view shows past cases, which cuts down a lot of back and forth and guesswork. I also find the initial setup to be moderately easy, and as an agent, it feels smooth and helps handle tickets quickly.
What do you dislike about the product?
One thing I was frustrated about DevRev is at least it logs out 3 to 4 times due to browser-related issues. These include too many tabs or heavy usage, cached data/cookies getting corrupted, unsupported or outdated browsers, and VPN or network restrictions.
What problems is the product solving and how is that benefiting you?
I use DevRev to manage customer cases like payment issues efficiently with automation and unified context, reducing back and forth and guesswork.
Financial Services
Centralized Tickets and AI Insights—Solid, But Needs More Differentiation
Reviewed on May 05, 2026
Review provided by G2
What do you like best about the product?
Centralizing customer support tickets and product feedback in one system so nothing slips through silos.
Linking feature requests and bug reports directly to engineering sprints and roadmaps.
Using AI‑driven analytics and conversational tools to get faster insights and automate routine tasks across teams.
Linking feature requests and bug reports directly to engineering sprints and roadmaps.
Using AI‑driven analytics and conversational tools to get faster insights and automate routine tasks across teams.
What do you dislike about the product?
Centralizing customer support tickets and product feedback in one system so nothing slips through silos.
Linking feature requests and bug reports directly to engineering sprints and roadmaps.
Using AI‑driven analytics and conversational tools to get faster insights and automate routine tasks across teams.
Linking feature requests and bug reports directly to engineering sprints and roadmaps.
Using AI‑driven analytics and conversational tools to get faster insights and automate routine tasks across teams.
What problems is the product solving and how is that benefiting you?
Centralizing customer support tickets and product feedback in one system so nothing slips through silos.
Linking feature requests and bug reports directly to engineering sprints and roadmaps.
Using AI‑driven analytics and conversational tools to get faster insights and automate routine tasks across teams.
Linking feature requests and bug reports directly to engineering sprints and roadmaps.
Using AI‑driven analytics and conversational tools to get faster insights and automate routine tasks across teams.