fake
progress
>ai agents (that finish)
>ml on your data
>full stack
>architecture rescue
>startups
>vibe coding
>qa & load
>scrum (no theatre)
// our team
0+
core engineers · we scale to 10 on demand
// proven delivery
0+
production projects shipped — and counting
// always reachable
0h
24-hour team access while your project is live
// time-tested
0+
years on the market · same core team
⏚About the name.
// why we called the company that
For years we've been joking about it inside the team. Every time a project needed a loader or a progress bar that doesn't really do anything, somebody would yell across the room — "just ship the fake progress". Hallucinated citations. Confident wrong answers. Bars that fill while nothing's actually happening. We've been laughing at it since long before there was a paper.
Then Carnegie Mellon turned our running joke into a benchmark.
REF: TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks — Xu, Neubig et al., Carnegie Mellon University, 2024–2025.
arxiv.org/abs/2412.14161
- setup
- a simulated software company on open-source tools (GitLab, OwnCloud, Plane, RocketChat). 175 real tasks across software engineering, project management, HR, finance and admin. Agents browse, write code, run programs, and talk to 16 simulated coworkers.
- scope
- twelve frontier models tested — the best from Anthropic, Google, OpenAI, Meta, Amazon, Alibaba. Real money, real API costs, run with the OpenHands agent framework.
// full task completion · 175 tasks
Gemini 2.5 Pro · Google
30.3%
Claude 3.7 Sonnet · Anthropic
26.3%
Claude 3.5 Sonnet · Anthropic
24.0%
Llama 3.1 405B · Meta
7.4%
Amazon Nova Pro · Amazon
1.7%
fake progress
So we named the company after the joke. It's a contempt-flag. Every time you see our name on an invoice or a Slack thread, you're seeing what we refuse to ship — the bar that fills while nothing happens. we ship the opposite.
⌬What we do
// services · 8 things we ship
Each tile below is something we've actually shipped this year. We don't list things we haven't built.
[ 01 ]
⌬ai agents & chatbots
Agents and chatbots tailored to your operations — support, document drafting, internal assistants, escalation flows. Built with proper evals so they fail loudly, not silently.
[ 02 ]
⏧ml on your data
Custom models trained on your own corpus — classifiers, scoring engines, recommendation, anomaly detection. Monitored, versioned, retrainable. No black boxes.
[ 03 ]
◇full-stack web
Web platforms end-to-end — UI, API, data, infra. Python, React, Postgres, AWS. Every system ships with tests, monitoring, and a runbook you can hand off.
[ 04 ]
⏚architecture rescue
Inherit a system that's choking and bring it back to life — refactors, redesigns, migrations. We take over projects other teams abandoned and ship them to production.
[ 05 ]
◈startups: mvp → prod
From idea to first paying customers and beyond. Senior engineers from day one — without the cost of a full team. Equity-friendly engagements for the right founders.
[ 06 ]
⌖vibe coding
AI-paired delivery for greenfield products and rapid prototypes. Several times faster than a traditional team — but with tests, docs, and observability. Same quality, half the timeline.
[ 07 ]
⎈qa & load testing
Real QA — manual, automated, and load. Find what breaks before customers do. Regression suites, load profiles tuned to your real traffic shape, and honest verdicts.
[ 08 ]
▰scrum & delivery
Honest Scrum and Kanban — real sprints, real risk logs, real burndowns. We run the delivery; you keep strategic control. No standup theatre.
⎈Last projects
// 5 of 10+ shipped · latest first · 2025–2026
A selection from our recent work. Real URLs where the work is public, real numbers from production.
PROJECT 01 :: visitweb
live · 9+ years
⌬VisitWeb — ad network with AI anti-fraud
100M+ ad shows/day·8 formats·9+ years live·our co-lead built it, sold it, still ships into it
problem
Ad networks bleed budget to bot clicks. ~12% of paid traffic was fake, refunds ran weeks behind the spend, and advertiser NPS sat at 6.
solution
A real-time AI verdict engine between every click and the invoice — 14 signals, 20M events/day, decided in 50ms, fakes blocked before they count.
results
~12% → ~2% ↓
bot traffic share
-70% ↓
advertiser refunds, y/y
6 → 9 ↑
customer nps, one quarter
PROJECT 02 :: redbus
pilot · scaling
⏧RedBus — route optimization for delivery fleets
logistics · fleets · last-mile·scaling 10 → 700 vehicles·commercial launch Q2 2026
problem
Planners burned 3–4 hours every morning routing by hand. Every order change forced a full re-plan, and fuel costs kept drifting up with no visibility.
solution
An engine that ingests orders, constraints and live traffic to produce routes in minutes — re-planning automatically, same code from 10 to 700 vehicles.
results
15 min ↓
daily planning, was 3–4 hrs
~$62k ·
per fleet/year saved
10 → 700 ↑
vehicles, same codebase
Q2 2026 ·
commercial launch
PROJECT 03 :: caemap
acceptance testing
⌖CAEMap — Roerich Expedition Atlas
problem
Roerich’s 1924–28 expedition left 2,000+ artifacts scattered across archives with no public access point — and the previous contractor walked off mid-build.
solution
We rebuilt the platform from scratch: an interactive map pinning every artifact to where it was made, with 3D landscape views — shipped for the 100-year anniversary.
results
2,000+ ·
artifacts, geo-anchored
100 yr ·
anniversary, on time
PROJECT 04 :: scorebazooka
live
◆ScoreBazooka — is this YouTube video worth your time?
problem
YouTube is full of clickbait, AI-generated noise and confidently-wrong content — with no fast way to judge a video before you spend the time.
solution
A Chrome extension that grades any video on six independent axes via specialized classifiers — truth, relevance, ad-density, ethics, uniqueness, human-vs-AI — in one click.
results
6 axes ·
truth · ethics · human · more
1 click ·
full report, no setup
2 of us ·
end-to-end build
PROJECT 05 :: kunama
live
⏚Kunama Translator — a low-resource language nobody else supports
problem
Kunama — spoken in Eritrea and Ethiopia — has zero support in any major translator and no public training corpus. Speakers lose access to tools everyone else takes for granted.
solution
We built a training corpus with native speakers, trained a model from scratch, and shipped a native offline iOS + Android app with flashcard learning built in.
results
1 language ·
unsupported by major ai
Offline ·
works without connectivity
iOS · Android ·
native, both stores
◇More we've shipped
Chess Academy Online — interactive chess school for beginners. AI sales-call quality control — auto-checks 100k+ calls/month for compliance. RAG agents on enterprise data — search and chat across messy Excels, ERP exports, and knowledge bases. Custom Telegram bots — onboarding, sales, ops, AI assistants for B2B teams. And more under NDA — ask us.