FORTISAI
FORTISAI
Automation, ML & Software Studio · Est. 2021

We are the build team. Engineers, ML and GenAI practitioners, and automation specialists who replace manual workflows, ship production-grade AI systems, and build the software in between.

40+
Systems & Automations Shipped
3wk
Avg. Concept To Live
99.9%
Uptime Across Deploys
Scroll
The Problem

Most builds
never survive contact with production.

A workflow still done by hand because "we will automate it later." A model that scored beautifully offline and fell over on real traffic. A codebase held together by the one engineer about to leave. Building the first version was never the hard part. Making it survive contact with reality is.

68%of repetitive manual workflows are still done by hand a year after teams plan to automate them
78%of AI pilots never reach production deployment
52%of internal software projects are abandoned before their first real user

“We had three models that scored beautifully offline and not one of them could handle a Monday morning traffic spike.”

VP Engineering, Series C SaaS Platform
Invoice Reconciliation Bot
Distribution Company
Shelved in month 4

Automated the happy path. Broke on every exception. Ops reverted to the manual process within a quarter.

SPENT $95KReverted to spreadsheets
Internal Support Agent
Retail Group
Shelved in month 9

Demoed flawlessly. Hallucinated on real tickets. Never left the staging environment.

SPENT $310K0 users
Internal Tools Rebuild
Mid-Market Manufacturer
Paused in month 8

A rewrite of the ops dashboard stalled halfway. The old system and the half-finished new one both run today, and nobody trusts either.

SPENT $220KTwo systems running in parallel
Never Shipped
What We Do

Three disciplines.
One build team.

Most studios pick a lane. We do not, because your actual problem rarely fits in one. The workflow that needs automating also needs a model behind it. The model needs a real application around it. We build all three, on the same team.

01 · Automation

Workflow Automation

We replace manual, repetitive processes with systems that run themselves: data entry, reconciliation, reporting, approvals. The busywork your best people are stuck doing by hand.

RPA & scripted workflows
Internal tooling & integrations
ETL & data pipeline automation
Approval & reporting workflows
02 · Machine Learning

ML & AI Systems

Models that survive real traffic, not just a holdout set. Evaluation harnesses, deployment pipelines, and monitoring built in from day one.

Production ML pipelines
LLM agents & RAG systems
Forecasting & classification models
Model monitoring & retraining
03 · Software Development

Custom Software

Full-stack systems built to be owned, not rented. APIs, internal tools, and customer-facing products, engineered by people who stay through the handoff.

Full-stack web applications
APIs & backend systems
Internal tools & dashboards
Legacy system modernization
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The Work

Real systems.
Real traffic.

Every engagement below runs in production today. Every number is measured post-launch, not on a holdout set. Clients are anonymized where contracts require it.

Q3 2025 · 7 week engagement

Invoice-to-payment automation processing 18.4K vendor invoices a year without manual matching.

Their AP team matched invoices to purchase orders by hand across three disconnected systems: the ERP, a vendor portal, and a shared inbox. Forty minutes per invoice, most of it copy-pasting line items. We built a reconciliation pipeline that pulls from all three sources, auto-matches on PO number and line-item totals, and routes only genuine mismatches to a human.

0.0K
Invoices Automated
0%
Manual Touch Time Cut
0.0K
AP Hours Saved
0%
Match Accuracy
Delivery Log · Regional Distribution Company
R
Regional Distribution Company
Shadow Run
Week 03

Pipeline matching invoices in parallel with the AP team. Every auto-match compared against the human decision before anything is trusted.

89%
Match Rate
71%
Auto-Routed
62
Invoices/Day
R
Regional Distribution Company
Production
Week 07

Full cutover. The AP team now only touches the 6% of invoices the pipeline cannot confidently match.

97%
Match Rate
94%
Auto-Routed
88
Invoices/Day
3WKS
The Process

Day one,
you're already in code.

No three-month discovery phase, and no six-week timeline either. We scope in days, build against your real data from day one, and put something in front of real users before most shops finish their kickoff deck.

Median Engagement
3wks
Kickoff → Production
3-4x faster than the industry average
Day 1-2

Scope & Data Audit

We look at your actual process and data before we promise anything. Half of what teams want automated is a script, not a platform, and we will tell you when that is the case.

Feasibility call, data access, and a written scope with a kill criterion.

01
Day 3-5

Thin Vertical Slice

One narrow path, end to end, running on real data. Not a notebook, not a mockup. A deployed service you can hit with a request.

Evaluation harness built before the build starts. If we cannot measure it, we do not ship it.

02
Week 02

Harden & Instrument

Failure modes, fallbacks, cost ceilings, and logging. This is the work that separates a demo from a system.

Tracing, cost budgets, graceful degradation, and human-in-the-loop escalation paths.

03
Week 02-03

Shadow Deployment

Live traffic, zero blast radius. The system runs in parallel with your current process until the numbers justify a cutover.

Side-by-side comparison against the human or incumbent baseline.

04
Week 03

Cutover & Handoff

Production traffic, and your engineers holding the pager. We write the runbooks and stay on call through the first cycle.

Documentation, maintenance schedule, and a team that does not need us next quarter.

05
Engagement

Let's Scope
Your Build.

Tell us what you are trying to build. We will come back with a scope, a timeline, and an honest read on whether AI is even the right tool for it.

Response within 1 business day. No sales deck. Just an engineer.

What Happens Next

No Deck.
Just A Working Build.

We do not send PDFs. We send an engineer. Here is exactly what happens after you hit submit. No discovery-call theater. No 40-slide proposal.

Day 1Technical scoping call. An engineer joins, not a salesperson.
Day 3Fixed-price scope and timeline, sent in writing.
Week 2First working build, running in your environment.
We Build With
PyTorchLangChainHugging FacevLLMpgvectorKubernetes