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Ask Reevo updates: Slack, artifacts & custom views. Explore the latest Ask Reevo updates, including Slack access, full-screen artifacts, custom views, and faster infrastructure for agentic sales workflows. Let's be honest about how most sales and revenue teams are forced to operate today. SDRs and AEs are assigned aggressive quotas, only to be immediately hamstrung by legacy software that turns them into glorified administrative assistants. They spend far too much time every week switching between 20 browser tabs, digging through drop-down menus, and playing hide-and-seek with pipeline data. That's why Reevo, Inc. is completely changing the dynamics between sellers and their data. Reevo, Inc. has just upgraded Ask Reevo so that it's an even better active, autonomous participant in your sales motion. Complex tasks are now as easy as prompting Ask Reevo in your natural language. Here's a look at the new capabilities Ask Reevo brings to your day-to-day. Ask Reevo in Slack, where you actually work. Sales and revenue teams live in Slack. This is where you communicate day-to-day, where the wins are celebrated, and where leadership asks for pipeline updates. But your actual data has lived trapped inside a separate system, forcing you to constantly bounce back and forth. That context switching destroys momentum. Not anymore. You can now send Ask Reevo a direct message in Slack, or @mention it in any channel. * Ask Reevo answers natural language questions about your accounts, pipeline health, or specific contacts. It delivers answers directly in Slack, complete with clickable links to the relevant records in Reevo. * Ask Reevo writes, too. Tell the agent to create a new task, update a deal stage, or draft a follow-up email. Ask Reevo surfaces an approval card in Slack, so the work is teed up and all you need to do is approve it. * Ask Reevo shares clean, long-form research because a deep dive into an account doesn't belong crammed into a tiny, unreadable chat bubble. When you ask for complex, long-form answers, you receive beautifully formatted inline text or a native Slack canvas that's easy to read and share. See the big picture with full-screen artifacts. Sometimes, you need to dig deep into a prospecting playbook, review a massive account research document, or analyze a heavily detailed sequence structure. In those moments, half of a browser window just doesn't give you the real estate you need to focus. Ask Reevo now features a seamless full-screen artifact toggle. When the agent generates a detailed asset, you'll see an icon in the top right corner featuring two outward-facing arrows. Click, and the artifact instantly expands to fill your entire screen for deep, distraction-free reading and editing. When you're done reviewing the document and ready to get back to the conversation, click the two inward-facing arrows to snap the artifact back into place and return to your standard chat view. It is full focus when you need it, and quick context when you do not. Build custom views without the headache. Building a custom report or a highly specific list view used to require an operations degree, a deep understanding of Boolean logic, and an incredible amount of patience. If a sales rep wanted to see a hyper-specific segment of their territory, they usually had to submit a ticket to RevOps and wait 3 days. With Ask Reevo, just say what you want to see. The agent builds a dynamic view with the exact filters, sorting logic, and data fields you need across any contact, account, or opportunity page. Want to see a highly targeted list? Just tell Ask Reevo: "I want to have a view that shows contacts from the last 2 months, that have a job title, and only show the email field." Ask Reevo instantly builds the view, applies it, and allows you to save it as a named view for continuous reuse. No endless drop-downs or broken logic. Just instant visibility into the data that matters. An upgraded sandbox powering what's ahead. To make all of this possible, Reevo, Inc. overhauled what happens under the hood. Ask Reevo's sandbox has received a massive infrastructure upgrade. Think of this upgrade as giving the AI agent its own high-powered personal computer. Because it operates on a significantly more robust infrastructure, artifact editing is now lightning-fast, and the agent can handle much more complex, multi-step workflows without timing out or losing context. But this infrastructure upgrade isn't just about speed today. It's the foundational layer that unlocks a wave of more agentic features in the very near future. So your agent just got smarter, faster, and much more capable of doing the heavy lifting. Let Ask Reevo do even more heavy lifting. By bringing Ask Reevo directly into Slack, delivering more tailored and immersive experiences, and upgrading its agent's infrastructure, Reevo, Inc. is entirely eliminating the friction between a sales team and its pipeline. If you're already running your GTM motion on Reevo, connect the Slack integration today and try building a custom view of your most neglected accounts with Ask Reevo. Watch how fast you move when the data finally comes to you. And if your team is still drowning in tab-switching and manual updates on a legacy sales stack, it's time for a clean upgrade. Take a self-guided tour, or book a demo with its team to see exactly what Reevo's unified, AI-native sales platform does for your win rates. Frequently Asked Questions: Ask Reevo A force multiplier for sales teams. Justin Herrick Jul 28, 2026 Key takeaways * You can send Ask Reevo a direct message in Slack, or @mention it in any channel. * When Ask Reevo generates a detailed asset, expand the artifact to fill your entire screen. * Say what you want to see, and Ask Reevo builds a custom view and saves it for continuous use. On this page

Reevo, an AI-native Revenue Operating System backed by Khosla Ventures and Kleiner Perkins, has acquired Ciro, a B2B prospecting agent. The company has raised $80 million in total funding. Ciro's technology automates prospecting for sales teams, using a multi-terabyte search index covering hundreds of millions of profiles. The agent finds, qualifies, enriches, and drafts outreach to contacts at scale, applying more than ten qualifying criteria per contact whilst learning preferences over time. The acquisition integrates Ciro's capabilities directly into Reevo's platform, eliminating the need for separate prospecting tools. This allows qualified leads to appear inside the CRM already enriched, scored, and matched to accounts, with outreach ready to send. Reevo has grown fourfold since its November 2025 launch and now employs over 90 people.

Automate the admin, not the relationship: how Reevo's agents made sellers 5x more productive. A seller spends 70 to 80 percent of the day not selling. Research, meeting prep, note-taking, follow-ups, CRM updates. The job has looked the same for 25 years, and most of it is administrative work the rep is bad at and resents. That was the starting point for Reevo's session at SaaStr AI 2026. Ali Ghotbi, the company's CRO and a 25-year veteran of technology sales, walked through how Reevo, an AI-native revenue platform, aimed agents at the administrative half of the job and left the relationship half to the human. The numbers he put on stage are big, and the logic behind where he pointed the agents is the part worth copying. The principle: don't make reps better at admin, remove it. Ghotbi was blunt about the tradeoff every RevOps leader knows. The best sellers are the worst at CRM hygiene. You hire them to be in front of customers and manage relationships, and that is exactly the work that does not belong to an agent. So Reevo did not try to make reps better at the administrative tasks. They built agents to take the tasks away. The decision rule is clean: automate the work that is high-effort and low-judgment, protect the work that is high-judgment and human. Meeting prep, hygiene, and follow-up drafting are the first; the live customer conversation is the second. Most companies bolt AI onto the wrong half and wonder why adoption stalls. Five agents on a single pane of glass. The rep logs into one place that shows quota, individual attainment, and team attainment. Around it sit agents that have either already done work and want to show it, or are asking to go do more. Ghotbi walked through five. **Meeting prep.**Tied to the calendar, the agent does deep research before each call, pulling from the public web and from the entire signal of that customer's history inside Reevo. It produces a prep doc with company context, the key stakeholders and their decision-making authority and style, recent news, a pain hypothesis, personalized icebreakers, discovery questions, likely objections with rebuttals, and meeting objectives. It is a living document that refreshes as new signals arrive, whether that is fresh public news or a recent email, so it is current the moment the rep walks into the call.**Deal progression.**The agent reads the CRM and flags deals losing momentum. In the demo it surfaced an Amazon deal with 15 days of no movement and no executive sponsor identified. When Ghotbi clicked in, it cited the evidence: last activity 15 days ago, three follow-ups with no reply, and a line from the call intelligence where the buyer said they needed to run it by someone in finance and no introduction was ever made. The agent had already drafted a personalized recovery email asking for that finance introduction. The rep just hits send.**CRM hygiene.**This agent works overnight, reading emails, activity, and conversations, then proactively filling the fields that never get filled: next steps, opportunity amounts, executive sponsors, the technology landscape. Ghotbi compared it to getting the rebound passed back so the rep can keep playing instead of chasing the ball. It also produces the clean, high-quality pipeline data that leaders actually want to make decisions from.**Deal disqualification.**Reevo does not let deals move to closed-won or closed-lost without human oversight, so this agent surfaces deals that look dead and asks the rep to disposition them, always with cited evidence. In the demo it pulled five. One Twilio deal had been in negotiation 90 days with zero engagement and three unanswered follow-ups, all synthesized from email history. Another, still in the sales-qualified stage, had gone quiet because, per a synthesis of email and LinkedIn, the buyer had left the company. The rep can then choose to restart with the new contact or close it out. Either way the pipeline gets clean.**Coaching.**A manager cannot sit on every call. This agent identifies where a rep is stuck, flags missing MEDDIC fields, surfaces objection-handling gaps, and recommends the next activity, like the Amazon recovery email above. What actually makes it work: the agent does the work and shows its work. The pattern across all five agents is the same, and it is the part most "AI for sales" tools miss. The agent does not hand the rep a suggestion to go act on. It does the work, drafts the artifact, and cites the evidence it used. The recovery email is written. The disqualification comes with the three unanswered emails attached. The hygiene fields are filled, not flagged for the rep to fill. And on the decisions that carry real consequences, closing a deal, abandoning an account, the human stays in the loop with a clear approve-or-reject. That combination, agents that do the work plus humans who own the calls that matter, is what lets a team trust the output enough to run on it. Same models as everyone, different result. Ghotbi made a useful contrast. Before, his team used OpenAI and Claude directly to write "personalized" outreach, and the messages all came out looking the same. The model was never the differentiator. What changed the output was the context layer underneath, the conversation history and the cross-platform signal that let the agent write something actually specific to the account. This is the same lesson that ran through the entire event. Everyone has the same models. The value is in the data and signal you feed them, and that is the part a competitor cannot copy by signing up for the same API. The results Reevo put on stage. By Ghotbi's account, the impact on his own org was large. His sellers became roughly five times more productive. The number of opportunities a rep could carry without the relationship degrading went from 10 to 15, which he assumed was the ceiling, to 50 to 75, with what he called zero leakage. And he was candid about the org consequence: he is behind on hiring, and the team hit its number with half the reps. These are a vendor's own stage figures, so treat them as Reevo's claims rather than an audited benchmark. But the direction is consistent with what other operators reported across the event, and the mechanism is sound. If you remove the administrative drag and give every rep current prep, clean data, and drafted follow-ups, capacity per rep goes up, and it goes up most for your best closers. What to steal from Reevo's playbook. If you are putting agents into a sales org: **Aim at the administrative 70 to 80 percent, not the relationship.**Automate high-effort, low-judgment work. Protect the live customer conversation.**Make prep a living document, not a one-time research task.**Tie it to the calendar and refresh it on new signals so it is current at call time.**Have agents do the work and cite the evidence, not just suggest.**A drafted recovery email with the reason attached gets used. A nudge to "follow up" does not.**Keep humans on the irreversible calls.**Close-won and close-lost should require an approve-or-reject with evidence, not an autonomous agent decision.**Fix CRM hygiene with overnight agents.**The perennial data problem is exactly the kind of low-judgment, high-volume task agents handle well.**Invest in the context layer, not the model.**The same models everyone has produce generic spam. Your conversation history and cross-platform signal are what make the output specific, and what make it defensible. Ad slot ready: 5887729102 Discover more Data Management Data Analytics Enterprise Technology