One engineer who tests the AI assistants you are pitched and tells you which to skip. Copilot, ChatGPT Enterprise, Claude, Gemini, and Glean all have a good demo, and most of the people showing it sell only one. We give your executive team an engineer who sets up a working assistant on your accounts and gives you a written recommendation for the company.
Bring the list of AI vendors you are already talking to.
Published results in executive teams
A government trial with 20,000 users and one bank's advisor rollout, with what each one needed.
20,000 UK civil servants using Microsoft 365 Copilot reported saving 26 minutes a day on average in a three-month trial.
A structured trial across 12 organisations. Savings were self-reported, and the report found limits on complex, data-heavy, and sensitive work.
98% of Morgan Stanley's Financial Advisor teams adopted its OpenAI-based assistant after the September 2023 rollout.
Six months from the March 2023 partnership to full rollout, built on the firm's own research and intellectual capital.
Figures as reported by the vendor or customer at the linked source. They are not OpenNash results.
Where our engineer comes in
The UK trial found real time savings and real limits on complex and sensitive work, and that is the useful part. You need the same answer for your company before signing a company-wide contract. Your engineer starts with the executive team's own work, the morning brief, board prep, and meeting follow-up, then uses what you actually relied on to recommend the rollout.
| Decision | What we look at | Outcome |
|---|---|---|
| Which company-wide assistant | Copilot, ChatGPT Enterprise, Claude, and Gemini, tested on your documents and security requirements, with the real per-seat cost. | A written recommendation you can take to the board. |
| Which vendor pitches to take seriously | The vendors already in your inbox, checked against what the general assistants already do. | A short list, and the questions to ask each one. |
| What the assistant can see | Inbox, calendar, drive, CRM, and Slack, approved one scope at a time. | Drafts by default. Sending or accepting needs your approval. |
| What stays in-house | Company knowledge, KPI definitions, and decision records. | Kept in your accounts, usable with whichever model you pick next year. |
Why forward-deployed engineers
Built for their largest accounts, deploying their own models. OpenAI's deployment company launched with more than $4B. ↗
Configure their own product, priced per seat or per resolution.
A small senior team, ex-Palantir, Meta, and Databricks. Any model, any vendor. Free pilot, then a flat monthly fee.
Even OpenAI closes the gap with engineers in the room. Source: OpenAI, What FDE means at OpenAI, Oct 2026.
The first eight weeks
Written down with your team in week 1. The pilot is free, and it has to pass these before anything goes further.
Example acceptance tests, not results from a customer deployment. Yours are written with your team.
Systems we work in
Rules from day one
FAQ
We start with the smallest approved scope, draft-only actions, and a log of every action. Your security team approves access before anything connects.
No. Prompts, test cases, and integrations are kept independent of any one provider, so you can switch when a better option ships.
An initial briefing, an access-approval session, and a short weekly review of what the assistant got right and wrong.
Why you need one
A senior engineer joins your team on a laptop you issue, tests the options on your data, and puts one executive teams workflow into production in 4 to 8 weeks. It starts with a free 14-day pilot judged against test cases you agree in writing.
After launch, we run and improve the workflow on a flat monthly fee, or your team takes it over. The code, tests, and runbook are yours either way.
Bring the list of AI vendors you are already talking to.