Aether · Enterprise AI Engineering · EST. 2020 · CALIFORNIA

AI that ships inside the systems you already run.

Aether designs, builds, and integrates production AI into your existing stack: agents, retrieval, computer vision. Senior engineers, fixed scopes, measurable outcomes.

Book a discovery call See how we work

30 minutes · an engineer, not a salesperson

YOUR SYSTEMS AETHER LAYER OUTCOMES CRM ERP DATA WAREHOUSE SUPPORT DESK RETRIEVAL AGENTS GUARDRAILS EVALS TICKETS AUTO-RESOLVED HOURS SAVED PER WEEK AUDIT-READY LOGS & EVALS FIG. 01 · INTEGRATION SCHEMATIC NO RIP-AND-REPLACE · WIRED INTO PRODUCTION SHEET 1 OF 1 SCALE: PRODUCTION

We build on · MODEL & CLOUD PLATFORMS

Anthropic Claude AI Anthropic
OpenAI GPT OpenAI
Google Cloud AI Google
Microsoft Azure AI Microsoft
Amazon AWS AWS
NVIDIA NVIDIA
Oracle Cloud Oracle
Salesforce Salesforce

Why teams hire us · 01

Most AI initiatives stall at the demo.

A prototype that wows the boardroom is the easy part. Getting it past security review, wiring it into a fifteen-year-old ERP, and proving it works on your real data. That is where projects die.

Aether is the production team. We audit your systems, scope a fixed engagement, and ship AI that runs inside your infrastructure, with the evals, guardrails, and documentation your auditors will ask for.

2–4 wks
To a working proof of concept
100%
Senior engineers on every project

Services · 08 CAPABILITIES

The full stack, as a spec sheet.

Strategy, data, models, integration, and the training to run it all without us. Every line links to the detail.

S.01 AI Staff Augmentation Agents embedded in your repos and queues that code, review, and ship around the clock. S.02 Enterprise Agentic AI Autonomous workflows that plan and execute across your software, with human checkpoints where they matter. S.03 AI Customer Support Voice and text agents for call centers: instant answers, clean escalation to humans. S.04 AI Training for Teams Hands-on programs for ChatGPT, Claude, Gemini, Copilot, and developer tools like Cursor. S.05 Computer Vision & Physical AI Detection, inspection, and video analytics running in real time on factory floors and job sites. S.06 Edge AI & SLMs Small language models deployed on-premise. Low latency, zero data egress. S.07 Generative Media Synthetic data, production video pipelines, and natural-sounding voice agents. S.08 AI Governance & Compliance EU AI Act and NIST alignment, evals, and guardrails that hold up in audit.

How we engage · 04 PHASES

Every phase ends with something you keep.

Fixed scopes, staged commitment. You can stop after any phase and walk away with the deliverable.

PHASE 01 1–2 wks

Audit & Discovery

We map your systems and data, and find the highest-leverage places to put AI to work.

You keepAn opportunity map and a fixed-scope proposal.

PHASE 02 2–4 wks

Prototype

A proof of concept built against your real data, not a slide deck, to validate feasibility and ROI.

You keepA working prototype and an honest go/no-go readout.

PHASE 03 6–12 wks

Implementation

Production engineering: integration, pipelines, evals, monitoring, and security review.

You keepA system in production, documented and observable.

PHASE 04 Ongoing

Scale & Optimize

Continuous tuning as your data and business change, plus training so your team can run it.

You keepDashboards, runbooks, and a team that owns it.

The full methodology

Field reports · CLIENT OUTCOMES

“We brought them in as staff augmentation for our ML backlog. Two engineers onboarded fast and shipped a production-ready ranking model in six weeks.”
James M. · VP Engineering · B2B SaaS
“We were skeptical about AI for ops. They built a small pilot, proved impact, then scaled it. Forecast accuracy improved ~9%.”
Ravi P. · VP Operations · National Logistics
“They worked within our security constraints and documented everything. Vendor review took days instead of weeks.”
Alicia T. · Security Lead · Enterprise Software

Results vary with data quality, scope, and operational readiness.

Read a full field report · FP&A forecast automation
SOC 2 aligned controlsSOC 2
Aligned
GDPR-ready data handlingGDPR
Ready
HIPAA-conscious architectureHIPAA
Conscious
ISO 27001 informed practicesISO 27001
Informed
Security posture, documented · Trust Center

FAQ · 04

Common questions

What is AI modernization?+
Integrating AI capabilities such as LLMs, computer vision, and predictive analytics into the systems and workflows you already run, to improve efficiency, automation, and decision-making without replacing your stack.
How long does an AI integration project take?+
A proof of concept typically takes 2–4 weeks. Full production implementations run 2–6 months depending on scope, data requirements, and integration complexity.
Do you work with specific industries?+
We work across FinTech, Healthcare, Manufacturing, Retail, Logistics, and more. The methodology is sector-agnostic; the models are built on your industry's data and edge cases.
What AI models and technologies do you use?+
Frontier platforms (Anthropic Claude, OpenAI GPT, Google Gemini) plus open-source models. We select per project for capability, latency, compliance, and cost.

Get started · 30 MIN

Talk to an engineer,
not a salesperson.

A free 30-minute technical consultation: your goals, your constraints, and a straight answer on whether AI is worth it for your case.

Book a discovery call

Prefer email? info@euforic.io

No commitment. No deck. Just engineering.