CampaignStack vs Reachy, compared for agencies

The local architecture is a coherent safety argument, not a cost cut. Because the app drives its own embedded browser on your machine, LinkedIn sees your usual IP and your usual hours, with no proxy in the chain and no session handed to a vendor, and Reachy is right that round-the-clock activity is a bot signature. The warm-up is enforced by the software rather than left to a blog post: a new account ramps to its recommended quota over about a week, with explicit status shown in the app. The commercial terms match the engineering honesty. Pricing is flat per seat with no usage credits, the 14-day trial takes no card, and the AI bill is whatever OpenAI, Anthropic or Google charge you directly, with 0% markup.

Reachy's homepage says it works while the app is open, not 24/7 from a cloud server, and for one founder that framing holds: the laptop is open when you work, and so is your outreach. It stops holding at agency scale. Fifteen accounts on the Agency plan means fifteen machines with the app running, and a campaign pauses whenever its owner closes a lid. The usual desktop escape hatch, renting a server per account, is closed here on Reachy's own terms, because moving the app off your machine and your IP would dismantle the safety story it sells.

CampaignStack keeps the human-pattern insight and drops the dependency: each account runs in a persistent, encrypted browser on our servers, paced to business hours in its own timezone, with per-action daily budgets and an automatic risk pause. Client campaigns advance whether or not anyone's laptop is open, and email runs alongside LinkedIn as a second channel, something Reachy does not attempt at any tier.

Reachy's generation half is real: it finds prospects from reactions, events and Slack communities, scores them against an ICP it detected from your website, and writes per-profile messages with whichever frontier model you plug in. What is missing is everything after the model answers. No automated check reads the draft, no approval step is documented before a sequence sends, and once sourcing is done nothing keeps watching those leads for the job change or funding round that would change the message. There is no public API or MCP server to script any of this in from outside.

That gap is where CampaignStack lives. A critic reads every draft against its full brief and objects before anything ships, doubtful drafts wait in a review queue where approving releases the send, and signals keep updating lead scores long after sourcing, gating who stays in a campaign. All of it is exposed through more than 300 MCP tools, so the agent story extends past writing the message to running the system, from the AI tools your team already uses.