New: The Incumbent's Advantage — a CTO's playbook for winning the AI era. Free PDF. Download now New: The Incumbent's Advantage — a CTO's playbook for winning the AI era. Free PDF. Download now

Production AI for systems that can't afford to fail.

Built by the team that's done it 150+ times since 2019.

Your next big idea is in good company

Partner AWS Machine Learning Partner
Partner Databricks Partner
Partner Funnel.io Partner
2019
AI-only since
150+
Projects Shipped in Production
$72MM
Business Value Created
50+
Companies Supported

Three steps. No surprises.

In a market full of vendors who sound the same, choosing wrong costs you six months you don't have. That's why we keep it simple:

1

Talk

30 minutes. No pitch deck. We'll tell you if we're the right fit — and if we're not, we'll say so.

2

Prove it in 5 days

We build a working prototype on your data, in your environment. You see results before you commit.

3

Ship it, own it

We build in your codebase, on your infrastructure. Everything we build, you own. No lock-in, no dependencies.

Book a discovery call

WE'VE SEEN THIS BEFORE

Sound familiar?

Every AI idea on LinkedIn sounds inspiring — until you need to put them in production.

Building a product

  • Board wants "everything AI" — your product can't afford to break
  • AI-native startups shipping features weekly — eroding your market share rapidly
  • Can't hire ML engineers — 6 months open, zero closes
  • Your last vendor claimed AI expertise but couldn't survive contact with production
  • Need a feature factory — but agencies own your IP
How we solve this →

Running operations

  • Repetitive back-office tasks burning labor and blocking capacity for new clients
  • Copy-paste workflows — an invitation to errors and inconsistent standards
  • Overwhelmed by "AI products" — none fit your specific use case or team
  • Tried no-code AI tools — none handle your real-world complexity
  • Want to adopt AI but genuinely not sure where to begin
How we solve this →

WHAT "TANGIBLE" LOOKS LIKE

5,000-page mortgage packages. 8 seconds. 95% precision.

LauraMac processes mortgage document packages — thousands of pages per package, hundreds of document types, noisy scans, inconsistent formats across states and years.

They tried other vendors. They tried building it themselves on AWS. Nothing survived contact with mortgage-grade compliance and precision requirements.

Softmax built a document intelligence pipeline that processes 5,000-page packages in 8 seconds. Split, classify, extract, verify, stack — all at 95% precision.

The engagement started four years ago. It kept expanding because it kept delivering. 80% cost reduction. And LauraMac's team owns everything we built.

"Within just three months, Softmax delivered a solution that accurately processes 5,000-page PDFs in only 8 seconds." — Amit Aggarwal, CTO @ LauraMac
See more stories →

Before us → After us

View all success stories →

WHY SOFTMAX

What you're actually hiring

AI-only since 2019

We were fine-tuning transformers before GPT-3 existed. Every engineer on our team builds production AI systems, full-time. We don't do web apps, mobile, or "digital transformation."

Production, not prototypes

We ship systems for clients with SOC 2, ISO 27001, and MISMO requirements — across multiple cloud platforms, with real latency and reliability targets. If your compliance team needs to sign off, we've done that dozens of times.

We build the infrastructure, not just the applications

Engram, our open-source context database for AI agents, is used by teams building persistent agent memory. You're hiring the team that makes the bricks — not just assembles them.

You own everything

Every line of code, every model weight, every architecture decision. Full documentation, runbooks, and training for your team. We build for handoff, not dependency.

What our clients say

Don't take our word for it. Here's what they say when we're not in the room.

Start with our interactive AI tools and free resources

Try them out, experience how we make AI work.

Quick bites from our blog

arXiv deep dives, agentic design patterns, fine-tuning tutorials, and production AI lessons — explained so any engineer can follow. New posts every two days.

SaaS

SaaS at a Junction Point: What we learned building AI in 2025

2025 has been an eventful year for most businesses. Tariff hikes, market volatility, renewed bubble talk—and, inevitably, everything AI. This year, we worked across mortgage, retail, real estate, and marketing—but the common thread wasn’t the industry, it was the economics. We built workflow automation for marketing agencies that lifted productivity by 12%. We deployed AI agents that helped retailers cut inventory costs while increasing turn rates. We consolidated fragmented data and built agen

LLM

Kimi 2.6 is out , more powerful than ever

Kimi K2.6 Tech Blog: Advancing Open-Source CodingKimi K2.6 advances open-source coding, featuring long-horizon coding, coding-driven design, agent swarms, proactive agents, and the Claw Groups research preview.baseten.co logomoonshotai/Kimi-K2.6 · Hugging FaceWe’re on a journey to advance and democratize artificial intelligence through open source and open science.Kimi AI with K2.6 | Better Coding, Smarter AgentsTry Kimi K2.6 to build stunning, full-stack websites, use Agent Swarm for massive ta

AI Agent

Paperclip vs OpenClaw: Not Just Another Agentic Orchestration Tool

Paperclip just crossed 31,000 stars on GitHub, and my timeline is full of people calling it "the future of AI companies." But scroll through the threads and you'll find a recurring question: isn't this just OpenClaw with extra steps? It's not. And the distinction matters more than most people realize. Having spent time with both projects, I want to unpack what Paperclip actually does differently — not at the feature level, but at the design philosophy level. How it thinks about progress, memor

A New Harness in Town: Meta-Harness

Meta-Harness: End-to-End Optimization of Model HarnessesMeta-Harness automatically optimizes model harnesses — the code determining what to store, retrieve, and present to an LLM — surpassing hand-designed systems on text classification, math reasoning, and agentic coding.Yoonho LeeMeta-Harness: End-to-End Optimization of Model HarnessesThe performance of large language model (LLM) systems depends not only on model weights, but also on their harness: the code that determines what information to

Your customers are waiting. Your board is asking.

Let's get something real into production. We've shipped 150+ AI systems since 2019 — in your codebase, on your timeline. Everything we build, you own.

Book a discovery call

30 minutes. No pitch deck. We'll tell you if we're the right fit — and if we're not, we'll say so.