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The AI your competitors will spend a year building. Yours in weeks.

Every product below started as one client's real problem — support costs eating margin, underwriting stuck in spreadsheets, GPU bills bleeding runway. We built the fix, proved it in production, and packaged it to deploy inside your business next.

800+Client projects since 2007
150+Engineers
24hReply time
armada / inferenceLive
142ms median latency, 30–75% cheaper than H100s.
shagl / publishLive
One brief in, nine channels out in 12 min.
open models / downloadOpen
Free to download, fine-tune and deploy.
voice agent / supportCase study
63% of calls resolved end-to-end by AI.
Industries covered: AI infrastructure B2B marketing teams Agencies Content-driven brands Open-source AI Healthcare Legal Insurance Banking Logistics Government Hospitality Retail E-commerce Multi-store chains Digital lenders Banks BNPL Microfinance Telecom Freight Supply chain Trade hubs Local food producers Farmers networks Regional marketplaces Agritech Hospital pathology departments Diagnostic labs Lab networks DTC beauty and wellness Subscription ecommerce Seasonal retail State agencies Government hotlines Public sector service centers
Technologies we build with
vLLM•TensorRT-LLM•OpenAI-compatible APIs•Intel AutoRound•RAG & LLM agents•OCR•Real-time voice AI•Neural recommendation models•Shopify•Whole-slide image analysis•vLLM•TensorRT-LLM•OpenAI-compatible APIs•Intel AutoRound•RAG & LLM agents•OCR•Real-time voice AI•Neural recommendation models•Shopify•Whole-slide image analysis•
The catalog

Pick a problem. The product for it is already running somewhere.

Every price below is a placeholder, final numbers depend on volume and deployment. Every link goes to the live product or a public case study.

AI Infrastructure
Armada

Production AI inference, 30-75% cheaper than datacenter H100s.

The problem

Teams running LLM workloads in production default to renting the same datacenter-grade H100 clusters built for training, even though inference has completely different economics: long idle stretches between requests, and none of the training-grade interconnect that GPU tier is priced for. That mismatch shows up directly on the monthly bill.

What we built

We built Armada on GPUs priced for inference instead of training — RTX 6000, RTX 5090, RTX 4090 and H20 — behind a drop-in OpenAI-compatible API. Every model runs on vLLM or TensorRT-LLM and scales to zero between requests, so idle time costs nothing instead of costing the same as a live request.

Success number
30–75%
cheaper than datacenter H100 inference, at 142ms median latency
Built for Any team running AI/LLM workloads in production
armada-navy.vercel.app →
Shagl product screenshot
AI Marketing Automation
Shagl

One narrative in, nine channels out.

The problem

Plavno's own marketing team hit the wall every growing B2B company hits: publishing consistently across channels takes constant drafting, formatting and scheduling, and that output is capped by headcount. It's the first thing that slips the moment the team gets pulled onto client work.

What we built

We built an engine that turns one narrative into channel-native drafts for nine platforms in a single pass — SEO-structured with metadata, headings, FAQs and internal linking, published through each platform's official API — with a human checkpoint before anything goes live.

Success number
12 min
from one brief to published and indexed across 9 channels
Built for B2B marketing teams, agencies, content-driven brands
shagl.xyz →
Open-Source AI Models
Open Models

Open LLMs, shrunk to run cheaply, free to download.

The problem

Serving the best-performing open checkpoint usually means buying more GPU capacity than the workload actually needs, because naive quantization either costs too much accuracy to trust in production or doesn't shrink the model enough to matter.

What we built

We compress open models with Intel's AutoRound method instead of naive rounding, calibrate every checkpoint on a language-balanced sample set, and publish exactly where the accuracy cost lands — so a team can pick W4A16 for raw speed or W8A16 for near-lossless quality, with the tradeoff already measured for them.

Success number
100+
downloads in the first week, free to run, fine-tune and deploy
Built for Any team self-hosting open-source LLMs
huggingface.co/plavno →
AI Voice Agent product screenshot
Voice AI
AI Voice Agent

Intake, scheduling and support, answered around the clock.

The problem

A regional insurer's support team grew alongside its customer base until call volume outpaced capacity — managerial call-backs were taking up to 40 minutes, which is untenable when the person calling is mid-claim and needs an answer now, not by end of day.

What we built

We built an AI voice agent that answers every incoming call as first-line support, resolving routine requests end-to-end on its own and routing anything complex to a human with the context already captured — so agents spend seconds accepting a handoff instead of minutes re-asking the same questions.

Success number
63%
of calls resolved end-to-end by AI, with an 84% first-call resolution rate
Built for Healthcare, legal, insurance, banking, logistics, government, hospitality
Case study: 24/7 insurance call automation →
Retail Recommendation & Forecasting Engine product screenshot
Retail AI
Retail Recommendation & Forecasting Engine

Personalized discovery, and demand forecasts up to 90% accurate.

The problem

An 83-store grocery retailer carrying 9,000+ SKUs had the inventory depth to support real personalization, but no way to act on it — every shopper saw the same generic best-sellers instead of products actually relevant to them, leaving demand and revenue on the table.

What we built

We built a recommendation engine using autoencoders and neural collaborative filtering, unifying online and offline purchase history into behavioral segments, then tuned the model's weighting against live A/B results until it consistently beat both random suggestions and simple popularity ranking.

Success number
3x
higher conversion on recommended products vs. random suggestions
Built for Retail, e-commerce, multi-store chains
Case study: AI-powered retail recommendations →
AI Credit Scoring & Underwriting Engine product screenshot
FinTech AI
AI Credit Scoring & Underwriting Engine

Loan decisions in minutes, not days.

The problem

Digital lenders were stuck with fragmented borrower data, credit decisions that varied from one underwriter to the next, and slow turnaround that hurt conversion at exactly the moment a borrower is comparing offers side by side.

What we built

We built a decision intelligence platform that blends predictive risk models, business-defined rules and human review into one workflow — pulling borrower data from multiple sources and returning an approve, decline or review recommendation with the reasoning attached, not just a score.

Success number
20–30%
faster underwriting, with 10–18% more consistent risk decisions
Built for Digital lenders, banks, BNPL, microfinance
Case study: AI loan underwriting platform →
AI Banking & Insurance Support Agent product screenshot
FinTech / CX AI
AI Banking & Insurance Support Agent

24/7 digital customer experience, without a night shift.

The problem

A retail bank's support team was fielding thousands of daily inquiries at an average 3.5 minutes each and only 150 calls per shift — mostly routine card, balance and product questions — while the country's 13 recognized minority language communities made consistent service even harder to staff for.

What we built

We built a conversational agent with real-time voice translation across 120 languages, OCR for document and photo recognition, and behavior-based cross-selling, automating balance checks, payments, card management and loan applications end-to-end with a clean handoff to a human for anything sensitive.

Success number
94%
cost savings on routine support tasks, with 61% faster handling time
Built for Banking, insurance, telecom
Case study: AI banking support chatbot →
Logistics Visibility & Exception Agent product screenshot
Logistics AI
Logistics Visibility & Exception Agent

One view of every shipment, and an agent that handles the exceptions.

The problem

Ops teams were tracking shipments across carrier portals, inboxes, spreadsheets and phone calls that don't talk to each other, so delays surfaced only after a customer had already asked where their order was.

What we built

We built a platform that unifies shipment events and carrier updates into one view, then runs an AI agent that flags delays, route deviations and documentation gaps automatically and routes each exception to the right team or carrier before it becomes a customer-facing problem.

Success number
1 dashboard
replacing carrier portals, inboxes and spreadsheets
Built for Logistics, freight, supply chain, trade hubs
Case study: Logistics visibility platform →
Local Food Marketplace Platform product screenshot
Marketplace AI
Local Food Marketplace Platform

One storefront network for every local producer, with AI-assisted discovery built in.

The problem

Local food producers and regional sellers across Virginia were selling through fragmented channels — social media posts, direct messages, basic order forms — with no shared storefront, weak product discovery across seasons and categories, and no consistent way to coordinate delivery zones or fulfillment between vendors and admins.

What we built

We built a multi-vendor marketplace that gives every producer their own storefront and dashboard, unifies catalog management, ordering and fulfillment into one operational layer for admins, and uses AI-assisted discovery to keep relevant local products surfacing as the catalog grows across seasons and categories.

Success number
One platform
replacing scattered social posts, DMs and order forms for every vendor
Built for Local food producers, farmers networks, regional marketplaces, agritech
Case study: Digital marketplace for local farmers →
AI Pathology Slide Triage Platform product screenshot
Healthcare AI
AI Pathology Slide Triage Platform

Every slide reviewed, urgent cases surfaced first.

The problem

Pathology labs are seeing case volume grow faster than specialist headcount, and every slide holds the same place in the queue whether it's routine or urgent — so the most time-sensitive cases wait behind everything else.

What we built

We built a platform that ingests whole-slide images, flags suspicious tissue regions with visual overlays, and ranks every case by clinical risk, so pathologists open the highest-priority slide first instead of just the next one in line.

Success number
Highest-risk first
every slide ranked and prioritized automatically
Built for Hospital pathology departments, diagnostic labs, lab networks
Case study: AI pathology slide triage →
AI Voice Commerce Assistant product screenshot
Voice AI / Retail
AI Voice Commerce Assistant

Order status, returns and subscriptions, answered before a human picks up.

The problem

A beauty and wellness retailer's support line got flooded with the same order-status and return calls every time a campaign or seasonal promotion landed, and phone coverage outside business hours couldn't keep up with the spike.

What we built

We built a voice assistant that holds a real conversation instead of routing through a menu tree, connected directly to Shopify order, shipping and subscription data — so it resolves tracking, returns and subscription changes on the spot, and hands off refund disputes to a human with full context attached.

Success number
24/7
coverage through campaign spikes and after-hours demand
Built for DTC beauty and wellness, subscription ecommerce, seasonal retail
Case study: Voice commerce for beauty retail →
AI Citizen Services Hotline product screenshot
Government / Voice AI
AI Citizen Services Hotline

Resident questions answered instantly, from approved information only.

The problem

A state agency's service center fielded the same eligibility, forms and deadline questions on every call, and staff spent so much time on repetitive information requests that answer quality varied from shift to shift and wait times climbed during filing periods.

What we built

We built a voice AI that answers resident calls using only approved government content, resolving routine questions directly and escalating anything sensitive or unresolved to staff with the full call context attached, so nothing gets an inconsistent or made-up answer.

Success number
Grounded answers
from approved content only, available to residents 24/7
Built for State agencies, government hotlines, public sector service centers
Case study: AI citizen services hotline →
How it works

Three ways to start, none of them a leap of faith.

01

Self-serve

Armada and Shagl are live products. Sign up, connect your data or stack, and start today, no sales call required.

02

Guided pilot

For the industry products, we scope a pilot against your own data first, so you see the fit before committing to a rollout.

03

Custom build

None of these an exact fit? We built all twelve from client work. We can build the thirteenth around your stack.

Let's talk

Tell us what you're trying to solve.

A Plavno expert replies within 24 hours, and we can sign an NDA before anything else.

Same team behind Armada, Shagl and the open models builds custom systems too.
800+ projects across healthcare, fintech, logistics and more since 2007.
sales@plavno.io Browse case studies →
Goes straight to our sales team. We reply within 24 hours.
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