Forward Deployed AI Engineering
Engineers in your repos.Shipping on your cadence.
PressW embeds senior AI engineers directly with your team. They join your standups, work in your codebase, and ship production AI systems alongside your people, with business context from day one.
Add AI Engineering Depth Without Adding Overhead.
Our approach
Forward deployed engineers work inside your environment, not from a distance. They sit with your subject matter experts, learn the business, and turn real workflows into working software.
Every PressW engineer is an AI engineer first. Our pods pair senior talent with AI-assisted development for testing, boilerplate, and deployment, so output scales without adding headcount.
We build so your team can own it. Code, documentation, and evaluation harnesses live in your repos, and knowledge transfer happens every sprint, not in a final handoff meeting.
POD STATUS · SPRINT 6
On trackSprint goal
Agent v2 to stagingPull requests merged
42Eval pass rate
94%Open blockers
1Next demo
ThursdayEMBEDDED IN YOUR STACK
7 of 8 connected
Your tools · your access policies · your review process
SPRINT REVIEW · OCT 2026
3 features shipped, 0 rollbacks
11
Stories closed
96%
Eval pass rate
4
Pairing sessions
Document triage agent promoted to production
Runbook added for on-call handoff
Put Senior AI Engineers Where the Work Happens.
Engineering services
Forward deployed pods flex to what your roadmap needs, from a single senior engineer to a full squad covering AI, data, and application work.
Embedded Engineering Pods
Small squads of senior AI engineers who join your standups, use your tools, and follow your release process. They ship on your timeline and scale up or down with your roadmap.
Agent & Workflow Development
Custom agents that read documents, call your systems, and complete multi-step work, with guardrails and human approval where judgment matters. Built and tested in your environment.
RAG & LLM Pipelines
Retrieval systems, vector pipelines, and prompt orchestration grounded in your data. We design for accuracy, latency, and cost, and instrument it all so quality stays measurable.
Evaluation & Quality Harnesses
Gold-standard examples, grading criteria, and regression suites that catch drift before your users do. Every system we ship comes with the evals that prove it works as intended.
Production Hardening & MLOps
Monitoring, logging, CI/CD, and rollback paths built for AI systems. We turn promising prototypes into stable production services your platform team can support.
Knowledge Transfer & Pairing
Your engineers pair with ours on real work, not slideware. Architecture decisions, runbooks, and code reviews are documented, so your team can extend the system after we step back.
Turn an Embedded Team Into Shipped Software.
Our process & impact
Forward deployed engagements are structured to deliver value early, keep you in control, and leave your team stronger than we found it.
01
Onboarded into your environment
Access, tooling, and security reviews come first. Within the first sprint, engineers are working in your repos, attending your rituals, and aligned on the outcomes that matter most.
02
Shipping from the first sprints
We move from discovery to working prototypes fast, then harden what works into production. Demos happen every sprint, so progress stays visible and priorities can shift when needed.
03
Owned by your team over time
Documentation, evals, and pairing build internal capability as we go. When the engagement winds down, your team runs and extends the system with confidence and a clear playbook.
Dive Deeper
Learn more about embedded AI engineering, agent development, and production AI from the PressW team.
Blog
Architecting LLM Systems for Chatbot Services & Intelligent Company Databases
Blog
Improving User Experience of LLM Applications through Streaming and User Engagement Tricks
Blog
Why Regulated Industries Need AI Agents, Not Just Automation
Simple automation breaks down in compliance-heavy environments. Here's why AI agents with reasoning capabilities are the future of regulated operations.
Add AI Engineers WhoShip From Day One.
Bring in senior AI engineers who work inside your team, deliver production systems, and leave your people ready to own them.
Embedded pods · Agents · RAG · Evals