Case studies

Shipped, measured, proven.

Real projects from our own product line and client work — each shipped to production, measured against hard targets, and still running today.

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~193ms

world-record latency

70%

tickets resolved end-to-end

$0

processing fees

$1.2M

saved in year one

Selected work

The proof is in the numbers

The AI++ · GoCX

Flagship product

World record · Broken

The AI calling agent that broke the world record

A real-time AI voice agent that listens, thinks, and replies in ~193ms — every model self-hosted on a single NVIDIA GPU with $0 API fees.

~193ms

perceived latency

28ms

TTS output speed

$0

API fees per call

193+

languages & accents

The challenge

Every incumbent stack in the voice-agent market routes calls through cloud speech-to-text, a cloud language model, and cloud text-to-speech. That chain takes 400–1500ms to reply and bills per API call — making natural conversation impossible and costs unpredictable.

The solution

We rebuilt the entire pipeline self-hosted and streaming. GPU voice-activity detection, streaming speech-to-text with partial transcripts, a proprietary reasoning model with speculative decoding, and a look-ahead voice engine — all on one GPU. Response caching serves greetings and FAQs in ~5ms.

“The gap isn’t small — it’s a different league. 193ms is what natural conversation feels like; everything else is a hold button.”

The AI++ Voice Team · Engineering

Key highlights

  • Self-hosted voice stack on one GPU
  • Voice cloning from a 30-second sample
  • Barge-in interruption support
  • Compliance built in: TCPA, GDPR, HIPAA, PCI-DSS
Voice AIReal-time streamingGPU serving
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The AI++ · AI Restaurant OS

Flagship product

Market record · Broken

The AI Operating System that beat the market boss

One system replaced Toast, Clover, Square and every legacy stack — 14 AI engines, 366+ integrations, and $0 processing fees. Not a POS app. An OS for the whole restaurant.

14

AI engines, one brain

366+

integrations

$0

processing fees

9/9

AI capability vs 0/9 rivals

The challenge

Restaurant owners run five disconnected tools — a POS, a scheduling app, a loyalty program, delivery tablets, and a phone line that goes to voicemail. Toast and the other market bosses charge 2–3% processing fees, lock owners into multi-year contracts, and score 0/9 on AI capability.

The solution

We built an AI operating system, not another app. 14 AI engines handle ordering, inventory, scheduling, reviews, and guest messaging under one brain. It runs on the owner’s existing POS hardware — no replacement, no data loss — and talks to guests across phone, WhatsApp, Instagram, and Snapchat.

“I keep my POS, keep my data, and get an entire AI back office. It replaced the market boss, not my hardware.”

Restaurant owner · AI Restaurant OS early customer

Key highlights

  • Your own POS keeps running
  • No data loss — existing database reused
  • AI agents answer calls, WhatsApp, Instagram, Snapchat
  • Custom websites & mobile apps for restaurants
Restaurant OSAI agentsZero processing fees
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SaaS platform

Client · Agentic automation

Agentic automation

Support copilot that cut response time from hours to minutes

An AI assistant that resolves support tickets end-to-end — 70% resolved without a human, with safe escalation built in.

70%

tickets resolved end-to-end

24/7

AI coverage

0

missed escalations

5×

faster first response

The challenge

A fast-growing SaaS team was drowning in repetitive tickets. Median first response was measured in hours, and the support team spent most of their day answering the same questions again and again.

The solution

We shipped a 24/7 AI copilot grounded in the product’s docs and historical tickets. It resolves routine issues end-to-end, escalates to a human with full context when it hits its limits, and learns from every resolved ticket.

“Our team finally works on the hard problems. The copilot took the busywork — and it keeps getting better every week.”

Head of Support · SaaS client

Key highlights

  • 24/7 AI agent with human escalation
  • Learns from every resolved ticket
  • Grounded in product docs via retrieval
LLMRAGReact
Talk to us about your stack

Enterprise legal & ops

Client · Custom AI application

Document intelligence

Document intelligence suite with 99.2% extraction accuracy

Extraction, summarization, and search across thousands of contracts per day — accurate, explainable, and reviewable by humans.

99.2%

field extraction accuracy

1,000+

contracts per day

0

unexplained results

3×

faster processing

The challenge

The team processed thousands of contracts daily with manual entry — slow, error-prone, and impossible to search. They needed accuracy they could audit, not a black box.

The solution

We built a pipeline combining OCR with layout parsing, semantic search over the extracted text, and human-in-the-loop review for the highest-stakes fields. Every extraction is explainable and traceable back to the source.

“Finally an AI system we can trust — it shows its work, and our reviewers can check it. That was non-negotiable.”

Operations Director · Enterprise client

Key highlights

  • OCR + layout parsing for scanned contracts
  • Semantic contract search
  • Human-in-the-loop review on key fields
PythonVector searchOCR
Talk to us about your stack

Logistics partner

Client · ML pipeline

Predictive analytics

Predictive demand engine that saved $1.2M in year one

A forecasting service that improved inventory accuracy by 34% and saved a logistics partner $1.2M in the first year.

$1.2M

saved in year one

34%

better inventory accuracy

0

missed rebalancing windows

24h

forecast refresh

The challenge

The partner’s inventory was driven by spreadsheets and guesswork — overstocking on slow items, understocking on fast ones. Wasted capital and missed demand cost millions quietly each year.

The solution

We built a real-time forecasting service with auto-rebalancing and live dashboards. The model ingests sales, seasonality, and supply data continuously, and surfaces the next-best action for every SKU.

“The dashboards pay for themselves. We stopped guessing and started deciding with data.”

Supply Chain Lead · Logistics partner

Key highlights

  • Real-time demand forecasts
  • Auto-rebalancing across SKUs
  • Live operational dashboards
MLOpsData pipelinesDashboards
Talk to us about your stack
How each story came together

The same loop, every time

Week 1

Find the real bottleneck

We measure where the time and money actually go before writing a line of code.

Weeks 1–3

Prototype on real data

A working demo against your own data — not a slide deck.

Ongoing

Instrument everything

Every build ships with evals and observability so improvements are measurable.

Week 6+

Ship and measure

Production launch, then we keep tuning against the metrics that matter.

Your case study is waiting to be written.

Bring us a problem. We’ll prototype, build, and ship — then measure the impact together.

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