StronglyAI is a production AI platform for enterprises, government, and SMBs stuck in pilot purgatory. 70-90% of AI projects never reach production. StronglyAI closes that gap with one platform - autonomous agents, AI apps, agentic workflows, an AI gateway across certified open weight models, and 500+ integrations - with Day Two operations built in from Day One.

What is the Strongly Labs Balanced Team?

The Balanced Team is Strongly Labs' cross-functional delivery team - data scientists, AI engineers, data engineers, full-stack developers, product managers and designers - who own delivery from discovery to production. They learn the systems, map failure modes, and build accountability into the engagement structure. The team stays accountable after launch - at month 7, when the novelty is gone and the business still has to work.

What can I build on the StronglyAI platform?

StronglyAI is one platform for production AI: autonomous agents, AI apps, and agentic workflows, an AI gateway routing across certified open weight models and every major provider, 500+ native integrations, plus governance, observability, and FinOps. Build no-code or with full Python and JS SDKs, then run it in production with Day Two operations built in.

What is Day Two in AI deployment?

Day Two is what happens after the AI demo is over and the room has cleared. It's when the pipeline breaks, the model drifts, and the vendor who sold the vision is unreachable. 70-90% of AI projects die at Day Two. StronglyAI builds Day Two operations - governance, monitoring, and workflows - from Day One, not retrofitted six months later.

How long does it take to see ROI with StronglyAI?

StronglyAI targets 3-6 month ROI versus the 12-18 month industry norm. This is achieved with pre-built workflow nodes and agent templates, governance built from Day One, and direct connection to existing CRM, ERP, and data systems without custom middleware.

What industries does StronglyAI serve?

StronglyAI serves enterprises, government agencies, and SMBs across financial services, insurance, healthcare, logistics, retail, manufacturing, IT, and banking. The platform deploys on-premises, in customer VPCs, or in private cloud environments with SOC 2 Type II compliance, HIPAA support, and FedRAMP-ready configurations.

Production AI

AI that still works on Day Two.

Agents, workflows and ML models on one platform, built with engineers who stay after launch. Run them in Strongly Cloud or your own environment.

Schedule A Demo Free AI Readiness Report

Production monitor Day 2

Runs today18,204

p95 latency640ms

Spend vs budget61%

Suit package assemblyWorkflowHealthy

Invoice extractionAgentHealthy

Churn forecastML modelHealthy

Support triageAgentHealthy

All workloads healthy. Guardrails, audit and budgets on every run.

Trusted by teams at

70-90%

of AI projects never reach production.

The demo works. Tuesday morning six weeks later does not.

0Suits a month

$0.00Per suit

Ours run. Every day.

Suit package assembly, in production at a creditor law firm, on the same team that did 200-300 a month before for $11 per suit.

See the Collections suite

How it works

Here's how we get you to production.

People, process, platform. In that order.

Step 1 People

Find the work worth automating.

Our engineers sit with your team, map how the work actually gets done and rank every use case on value and level of effort. You start with the one that pays back first.

Free AI readiness report to start
Forward Deployed Engineers inside your operation
Ranked by value and level of effort, not a slide deck

Use cases: value vs level of effortRanked

Start here

Level of effortHighLow Value Suit packages Invoice extraction Demand forecast Meeting notes Org chatbot

Invoice extractionBuilt in weeks

Inbox

Agent

Guardrails

Human
review

ERP

Visual builderPython SDKJS SDK

# same workflow, from code wf = strongly.workflow("invoice-extraction") wf.guardrails(pii="redact", budget="$400/mo") wf.review(when="confidence < 0.9")

Step 2 Process

Build it with Day Two already in it.

Agents, workflows and models are built with guardrails, review steps and budgets from the first commit. Your analysts use the visual builder. Your engineers use the SDKs. Same governance either way.

Visual builder, Python and JS SDKs
PII filtering, policies and human review built in
Connected to 500+ systems

Step 3 Platform

Run it. We stay for what breaks.

Monitoring, cost controls and audit run on every workload. When a model drifts or a source system changes, it is caught and fixed. At month seven we are still there.

Observability and drift alerts on every run
FinOps budgets per agent, team and model
Audit logs and role-based access throughout

Operations, Month 7All healthy

Workloads12

Uptime99.9%

Reviews3.1%

Spend this month62% of budget

AlertInvoice extraction accuracy dipped after a vendor changed their template.

FixTemplate added, rule updated, 214 invoices re-run.

ResolvedBack above threshold. Change logged to the audit trail.

Who it's for

Three ways in. One standard.

Board mandate

The board said do AI. Nobody said how.

We find the first use case worth doing, build it and put it into production, with the numbers to take back to the board.

Get the readiness report →

Use case ready

You know what to build. You need it delivered.

Forward Deployed Engineers build it with your team on the platform, then stay to run it.

See use cases →

Technical team

You know MLOps. You need platform depth.

One platform for GenAI and classical ML, in your cloud, on-prem or air-gapped, with the controls your security team asks for.

Explore the platform →

Why Strongly

Build it yourself. Or don't.

A straight comparison.

Run the ROI Calculator

	Build it yourself	With Strongly
Time to ROI	12-18 months	3-6 months
Platform team	2 cloud engineers, plus 1 for every 5 workloads	Platform run for you
Day Two	Retrofitted after launch	Built in from day one
Models	One provider at a time	Open-weight and every major provider, one gateway
Where it runs	Wherever you stand it up	Strongly Cloud or your environment, including air-gapped
After launch	Your team, alone	Engineers who stay

Industry norm vs Strongly target time to ROI. Platform team sizing from the ROI calculator assumptions.

Timeline

From first call to production.

Days of diagnosis

Readiness report, workflow mapping and a ranked list of use cases.

Weeks to production

Your first workload live, governed and monitored, on real data.

Months of compounding

Every workload after the first ships faster on the same platform, controls and team.

Team

Built by engineers who've done this before.

Founded by three operators with deep experience shipping production AI.

0Years combined experienceEnterprise data platforms, analytics and production AI and ML.

3Industry veteransBuilt and scaled enterprise technology companies to exits.

0Organizations servedFrom SMBs to enterprises and government agencies.

Meet the Team

By Our Chief AI Officer

Leading Through the AI Revolution

The book for leaders who refuse to be the statistic - the C.H.A.R.T. framework for turning AI pilots into production, plus a 180-day action plan.

Read the introduction

FAQ

Questions buyers ask.

One platform to build, run and govern AI agents, workflows and ML models, with engineers who get them into production and stay. It runs in Strongly Cloud or your own environment.

You can. Most teams spend 12-18 months standing up the platform, the controls and the monitoring before the first workload pays back. Strongly gives you all of it on day one, so your engineers spend their time on the use case.

No. Analysts build in the visual builder and our Forward Deployed Engineers work alongside your team. If you have engineers, they get full Python and JS SDKs on the same platform.

Strongly Cloud, AWS, Azure, GCP, on-prem or air-gapped. Data stays in the environment you choose, and open-weight models can run there too.

With the free AI readiness report or a demo. We rank your use cases, agree the first one and put it into production.

Start with the work that matters.

We'll show you which use case pays back first, and what it takes to run it.

Schedule A Demo Free AI Readiness Report