Hashlogics
Answers

Can a small or mid-size business get a forward deployed engineer?

The labs' FDE teams go where the contract is biggest. What you're actually after is the way they work, and that travels.

Answered in short

4 things that decide this

  1. 01Yes, a small or mid-sized business can get a forward deployed engineer, but rarely from an AI lab. Those teams are small (OpenAI's began in 2025 with two engineers, per The Pragmatic Engineer) and are assigned to large accounts. The same working method is available to smaller companies through a senior engineer embedded from a partner firm.
  2. 02What you're buying is the motion, not the badge: an engineer who sits in your operations, builds on your systems and your data, and stays until the thing runs and someone on your side owns it. That's what a forward deployment is, and it doesn't need a lab's letterhead.
  3. 03Hashlogics runs this engagement for mid-sized firms and funded startups. A senior engineer joins your repository and your standups, ships into live operations in increments, and the engagement ends with a trained owner or a service level. You interview the engineer before they start.
  4. 04The fit test is short. You have a live process the software has to change, someone on your side who can make decisions weekly, and a system of record it has to write to. If all three are true, an embedded engineer works. If none are, you need a product, not a person.
The labs

Why a lab's FDE team won't come to you

A forward deployed engineer is a senior engineer the vendor assigns to one account. That's expensive for the vendor, so it goes where the contract justifies it. The Wall Street Journal's October 2025 piece on AI startups using FDEs framed them as a way to win enterprise deals, and Wikipedia's example is a vendor embedding an engineer 'for a few months' with a customer buying its AI product.

There's a second limit that matters more than size. A vendor's FDE ships the vendor's product. Palantir's own description puts its Deltas inside Business Development, with a mandate 'to achieve technical outcomes for our customers' on Palantir's platforms. That's the right loyalty for the vendor. It's the wrong one if what your process needs is a small custom system, an integration between two tools you already run, or no new product at all.

An engineer embedded from a partner has no product to sell you. Their job is whatever makes your process run, which sometimes means telling you not to buy the thing you called about.

At your size

What the same motion looks like for a mid-sized company

You meet the engineer first. Every engineer we place is interviewed by you before they start, and you can decline anyone. From the first week they work in your repository, join your standups and get at least four hours of overlap with your working day, agreed before anyone starts. Your engineers review their pull requests; there's no delivery manager in between.

They ship into live operations, not into a staging environment nobody uses. For Sutherland Excavating, that meant AI and IoT site management running across real petroleum sites. ZhoopZhoop got an AI receptionist and parts ordering working inside a multi-branch auto repair business. Little Tree, an artisan bakery, got an n8n automation that turns meetings into actions. None of those came from a generic product and a manual; each was built on the client's own workflow.

The engagement ends on purpose. Either your team is trained to own the system, with runbooks and a handover, or it stays under an agreed service level with us answering when it breaks. Code, prompts and pipelines are yours from the first commit either way. Scoping calls are free. A paid two-week diagnostic applies only where we have to go into an existing codebase to give you an honest answer, and it ends in a fixed price.

An embedded engagement, start to finishLive
  1. ScopeFree call: what's stuck, and what has to change.
  2. InterviewYou meet the engineer; you can say no.
  3. EmbedYour repository, your standups, your review.
  4. ShipInto live operations, in increments.
  5. OwnTrained owner on your side, or a service level.

Same shape as a lab's forward deployment, without the product the lab needs you to buy.

Questions, answered
01Do we need to have bought an AI product first?+

No. An embedded engineer from a partner isn't tied to a product, so the engagement can start with your process and pick tools afterwards, or use the ones you already run. That's the main difference from a vendor's FDE, whose job is to deploy the vendor's platform. If a packaged product turns out to be the right answer, the engineer integrates it; if not, they build what's missing.

02Is this the same as staff augmentation?+

It's the engagement we run under that name, with two things a body-shop version doesn't include: the engineer ships into your live operations rather than filling a seat, and the engagement ends with a trained owner or a service level rather than a departure. You interview every engineer first, they work in your repository under your review, and the code is yours from the first commit.

03How do we know if we're too small for this?+

Size matters less than three conditions: a live process the software has to change, someone who can make decisions weekly, and a system of record to write to. A ten-person firm with all three is a better fit than a five-hundred-person firm with none. If you only have a question and no process yet, start with a free scoping call rather than an engagement.

Updated
Start

Let’s deploy working AI into your business.

We build AI agents and automation, ship them into the tools you already run, then stay on under an agreed service level. A senior engineer reads every brief, and your call gets scheduled within 24 hours.

What happens next

  1. 01

    You send a brief or book a call

    Two minutes, whichever you prefer.

  2. 02

    A senior engineer replies within 24 hours

    Not a sales rep.

  3. 03

    Honest scoping, in writing

    And if we’re not the right fit, we say so.

Abdul Basit, CEO of Hashlogics

“I started Hashlogics because too many teams ship a demo, get paid, and disappear. We build to a standard we’d run ourselves — and we stay to keep it running.”

Abdul Basit · CEO · a direct line

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