Sociali.ai wanted a platform where one marketer could run social media for a hundred brands. A five-person Dataspecc pod (a PM, two full-stack engineers, an AI engineer and QA) built the whole thing: the app, the AI behind it, and the testing that keeps both honest.
Agencies and franchise-style organisations manage dozens or hundreds of brands. Each one needs its own voice, calendar and approvals, and posting to every network by hand doesn't scale.
A platform where AI plans a month of content per brand, writes and designs every post, re-brands it for each location, routes it through approval, and publishes on schedule.
As one managed pod with a single point of accountability. Our PM owns scope and cadence, and QA is built into every release rather than bolted on at the end.
Scoped with the founders and delivered as releases, with testing built into each one.
A monthly plan for each brand and channel, built from the brand's own website, trends and holidays.
Turn a month of ideas into finished posts in bulk: captions, hashtags and creatives, ready for review.
Posts are designed in an embedded editor with AI image, video and voice generation, with no switching to another tool.
Duplicate a campaign across brands and the logo, colours, fonts, images and caption change to match each one.
Reviewers and approvers sign off before anything goes live, with digest emails so nothing sits waiting.
A chat-based strategist that studies the brand, agrees a strategy, then produces and checks the calendar itself.
The problems that decide whether a product like this ships at all, and what solving each one means for the people using it.
Generated posts drift off-brand, and generated images come out with extra fingers and garbled text.
Every step of generation (caption, hashtags, image) is reviewed by a second AI acting as judge, and sent back until it passes. A vision check scores each image for defects before a human ever sees it.
Fewer rejected posts, less human cleanup
A multi-location business wants one campaign in every location's own branding, not the same post copied a hundred times.
The duplication engine rebuilds each design for every target brand and channel, swapping logo, colours, fonts, images and caption, and checks the design will carry over cleanly first.
One campaign becomes a hundred on-brand posts
Social APIs fail in ambiguous ways. A naive retry double-posts; no retry misses the slot.
Each scheduled post is a durable job that waits for its moment, survives edits and cancellations, and checks the account is still connected before firing. Instagram publishing records each stage, so a retry can never post twice.
No duplicate posts, no silent misses
Facebook, Instagram, LinkedIn, Threads, TikTok and Google each fail, rate-limit and expire tokens differently.
All six go through one shared layer that retries sensibly, stops on permanent errors and backs off when a platform is struggling. Connections are checked on a schedule, so users hear about an expired login before a post fails.
Problems caught before the customer notices
With AI in the loop, "it worked when we tried it" isn't a release standard.
Around 800 automated test files cover the app and the AI service, with end-to-end browser tests on every pull request. Generated captions, ideas and designs are scored automatically in production, so a model change that lowers quality shows up in the numbers.
Every release tested; AI quality tracked live
Chosen per layer for the job, with managed services wherever they save the client engineering time.
InstagramOver the years, though, we've just developed so much trust… they almost feel like business partners… I hope to be in business with these guys forever.
Commissions, P&L reporting, analytics and AI-generated leads in one internal platform, used by 100+ recruiters at a multi-million-dollar recruitment firm.
Point at the case study closest to your problem, or just describe it. You'll talk to an engineer from the bench that built these, not a salesperson.