Defense
Physical AI and employable agents for constrained, high-stakes environments.
Technology Partners·Anthropic·OpenAI
AI that works after the demoAI that works
AI that works
on Day Two.
And every day after.
Day One is the demo that wows everyone. Day Two is the hard part: getting AI to actually work inside your real business. We're like a building contractor for AI: we assemble a custom system from proven tools, install it in your environment, and stay on.
Why now
Day One is getting easier. Day Two is still hard. Cheaper development gives you unprecedented customization, but integration and deployment were never a vibe-coding problem.
- 01Generic platforms don't bend to regulated or underserved workflows.
- 02Coding agents compress build time for custom software and integration.
- 03Open-weight models make private, edge, and hybrid deployment practical.
- 04Buyers already believe in AI. They need systems that hold up inside real constraints.
Custom-built · not off-the-shelfYour systems · your data
Defense · Manufacturing · Public Service · Enterprise Tech
In Production
Running in Fortune 500 manufacturing environments today.
Partnerships
Active partnership tracks with core model and infrastructure providers.
Founding Team
Enterprise AI deployment in high tech and manufacturing over 10+ years.
Why Us
The current options are products. Not solutions.
Generic SaaS misses your proprietary workflows. Frontier platforms assume your data flows into their ecosystem. DIY creates tech debt and security exposure. Integrators are slow, expensive, and billed by the hour. Here's what we do differently.
01 · Compounding Components
Pre-built components. Faster delivery, lower cost.
02 · Outcome-Based
Pay for outcomes. Secure, cost-effective, built for you.
03 · Full Ownership
You own the system. No lock-in, ever.
How We Work
The DayTwoAI Model.
Three working habits we bring to most engagements. They're how we think about Day Two, not a fixed checklist.
Step 01
Scope Week
A paid, one-week discovery sprint. We define the outcome, map the systems involved, and propose the delivery path: sprint track or SOW. You leave with a clear proposal either way.
Step 02
Sprint Delivery or SOW
Sprint track: 2-week delivery sprints, each with a defined output. SOW track: for broader, multi-system scope, fixed price, milestones agreed before we start.
Step 03
Day Two Support
Ongoing support scoped during the engagement, not bolted on after. Monitoring, retraining, evolution, built into the plan from day one.
We build for production, not for the slide deck. Day Two is baked in from day one.
Day Two, designed inThe Building Blocks
We deploy from a library of production-tested components.
Every engagement assembles from components we've already built, tested, and deployed. Faster time to production. No reinventing the stack.
01
maya
Multi-agent, multi-provider orchestration harness.
02
niti
Agent policy enforcement: cost, control, and guardrails near the source.
03
distillx
Context harvester, extracts and routes signal from unstructured sources.
04
readybase
Codebase intelligence and AI-readiness analysis. Hosted at promptforce.ai.
05
prefex
Model routing and output-shaping layer.
Solutions
Three domains. One operating philosophy.
Each engagement starts with the outcome you're after, and aims at a system that helps produce it, in your environment, on your stack, against your data.
01 · Physical AI
Physical AI
Vision, robotics, and automation for cost-of-quality problems.
Manufacturing · Defense
- Defects caught before they become scrap.
- Robotic arms, sensors, and PLCs working from one system.
- Inspection that runs on the edge, MLX and Nvidia hardware.
Legacy Reality01 · 03
02 · Tokenomics
Tokenomics
Hybrid inference and cost-to-serve, engineered not guessed.
Enterprise Tech · Defense
- Inference cost brought under control as usage scales.
- Local and cloud models routed by cost and sensitivity.
- Hybrid architectures that don't lock you to one vendor.
The Problem — Data Graveyard01 · 03
03 · Employable Agents
Employable Agents
Agents with cost controls and guardrails, not just capability.
Defense · Public Service · Enterprise Tech
- Agent spend and behavior bounded before deployment.
- Guardrails enforced near the source, not bolted on after.
- Local or hybrid models depending on what the environment allows.
Individual Tool Chaos01 · 03
Industries
Operators who own outcomes.
We work directly with the people on the hook for the result, building together with the team who lives with the outcome every day after.
Manufacturing
Vision inspection and agentic BI on the shop floor.
Public Service
Compliance visibility and agents with guardrails built in.
Enterprise Tech
Hybrid inference and cost-controlled agent deployment.
Showcase
Working demos. Built from our blocks.
Live demos of what we build. Try them.
Demo · Physical AI
Sink or Float
Two bottles, same size, both painted solid. One is full of heavy bits, one is empty. A kid picked them up and answered in about a second. The camera said SINK for both: the answer is inside the bottle, where a photo cannot reach.
The tactile gripper got both right. It measured 3.2 mm of give on a 23.9 mm bottle. Give means air, and air floats. Neither half gets there alone: the gripper needs the camera to tell it how wide to open. Vision has had twenty years of attention. Touch this good is new, and it was the half that was missing.
Built with Contactile
Read the write-up, including what broke
Legacy Reality01 · 03
Demo
Vision Inspection Agents
Edge inference on MLX and Nvidia hardware, integrated with robotic arms, sensors, and PLCs.
Engagement Model
Priced around outcomes, scoped per project.
We don't list packages or per-seat tiers. Every engagement is scoped against the specific outcome you're trying to reach, the systems involved, and the shape of the team we'll work with. Pricing follows from that, discussed openly and agreed before we start.
Discovery starts with a Scope Week01
Start with a Scope Week.
One week, fixed scope. We map the outcome, the systems, and the delivery path. You get a clear proposal regardless of whether we proceed.
02
Deliver in sprints or a fixed SOW.
Sprint track: scoped deliverables on a 2-week cadence. SOW track: fixed price, milestone-based, agreed upfront for broader scope.
03
Day Two support is designed in.
What the system needs after launch, monitoring, retraining, evolution, is scoped during the engagement, not negotiated after you depend on it.
Contact
Day Two starts with one conversation.
Tell us the outcome you're trying to produce. We'll read it, think on it, and come back with what a real conversation would look like.
Emailcontact@daytwoai.com
ResponseUsually within a few business days
FormatEmail first, call if it makes sense
EngagementsScoped per project
OUTCOME MATTERSEvery engagement starts with what success looks like for you.