Different in kind, not just in degree
Rogo is a capable, finance-native AI platform. Built by former bankers and investors, its agents, led by one called Felix, execute multi-step workflows end to end: deal screening, comparable transactions, CIM generation, diligence memos, buyer outreach. It connects into firm systems like SharePoint and CRM, pulls on market data and filings, and produces institutional outputs a firm can actually use. That is a real and useful capability, and it is the whole point of the tool.
What's different is the shape of the product. Rogo is built to do the work: you give it a task, it executes, it hands back a deliverable. What it isn't built to be is the durable, structured place that work lives in afterwards. There's no standing ontology of "this deal, this contact, this organisation" that accumulates context over time, links every fact back to its source, and stays in place long after the task is done. The deliverables are excellent; the persistent firm-wide record underneath them is a different job.
DealSage starts from that other end. Before any deliverable gets produced, your firm's deals, contacts, organisations and documents are structured into a configurable ontology, with every field carrying source lineage back to the page or line it came from. And the CRM, pipeline and deal library aren't separate tools bolted on, they're apps that run on that same record. That's the platform: not a faster way to produce a memo, but a standing model of your firm that every answer, and every future answer, can draw on.
Where Rogo is the better fit
If the job in front of you is genuinely to produce analyst work, and produce a lot of it, quickly, Rogo is built for exactly that and does it well. Drafting a CIM, pulling a comp set, turning a data room into a diligence memo, generating a first-cut model: these are the tasks Rogo's agents are designed to execute, and the outputs are meant to be institutional-grade, auditable rather than black-box. For a team whose bottleneck is analyst hours spent producing deliverables, that is a direct answer to a real problem, and the team behind it suggests it holds up at real firms.
It's worth being honest about the edges too. Rogo is sales-led with no published pricing and bespoke, white-glove deployments, so you won't get a number without a conversation. Its security page describes encryption, siloed per-customer environments and a no-training-on-your-data policy, but it doesn't publish a VPC or on-premise option, so cloud is the deployment path on offer. None of that rules Rogo out for the job it's built for. It just means the job needs to actually be producing deal work, not being the system of record for the firm.
Where DealSage is the better fit
If what you actually want is for your firm's knowledge to compound, so that an answer from a deal three months ago is still linked to the one you're working today, without anyone regenerating it, that's a different requirement, and it's the one DealSage is built around. The ontology holds Deal, Contact, Organisation and any custom objects your firm needs, with field-level lineage so every number traces back to its source document. The CRM, the pipeline, the deal library all run on that record, so the place you produce work and the place you operate the firm are the same place.
It also reaches you differently. CC the DealSage agent on an email thread and get a cited answer back. Pull a sourced figure straight into a live-linked Excel cell. Connect over MCP so Claude, ChatGPT or whichever model you prefer can query the same knowledge base. And because deployment isn't cloud-only, firms with stricter data residency or security requirements can run DealSage in their own VPC or fully on-premise, an option Rogo doesn't publish. Implementation runs through an embedded team, consultant, technologist and builder, so the ontology is live in weeks. Our security posture is verifiable at trust.dealsage.io.