OmniCognit.
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AI deployment & technical advisory · remote, worldwide

Most AI pilots die at the demo. Ours ship, because we scope them small enough to finish.

One system you already use. A language model inside it. Proof that it works on your real tasks — and documentation, so it still works after we leave.

Tell us what you run See exactly what that means

$3,000 fixed for a first deployment. $500 a day after that. No retainers held.

What we do

The hard part was never the model.

If you have already run an AI pilot that went nowhere, you know how it happened. Someone built something impressive in a sandbox. It never touched the CRM. Nobody wrote down how it worked. The person who built it moved on, and six months later it was quietly switched off.

That is not a model problem. Models are good now, and getting better without your help. The failure is in the boring middle: connecting it to the systems your team actually opens, testing it against work you actually do, and leaving behind documentation someone else can pick up.

So that is all we sell. We do not run innovation workshops or write AI strategy decks. We take one system you already use, put a language model inside it, prove it works on your real tasks, and write it all down.

What we take on
  • Assessing your infrastructure, data and readiness before anything is chosen
  • Selecting and configuring a model against your actual tasks
  • Integrating it with the systems and workflows you already run
  • Designing the data pipeline for training and inference
  • Testing and tuning against your real work, not a public benchmark
  • A four-hour live training session with the people who will use it
  • Written API reference, user manuals and setup guides — yours to keep
  • Security review: encryption in transit and at rest, data handling, compliance
What we will not do
  • Train a foundation model from scratch on your data
  • Sell you GPU infrastructure you do not need
  • Replace your team, or advise you to
  • Run an open-ended “transformation programme” with no defined end
  • Deliver anything we cannot hand you documentation for
  • Work outside a signed scope — including work you ask for mid-project

“Does our data leave our environment?”

Everyone asks this first, and anyone who answers immediately is guessing. It depends on what the assessment finds. The model can run in your own cloud account, in ours, or against a hosted API — and those three have very different cost, latency and data-residency profiles. You get all three written down, costed, with the one we recommend and why, before a single thing is installed. Your data is securely destroyed when the engagement ends, confirmed in writing.

Services

Three things you can buy. Nothing else.

Each one says what it is, what it produces, and how it is priced.

Deployment

A language model installed and integrated into one of the business systems you already run — configured, connected, tested against your work, and documented. The scope is agreed and fixed before it starts, which is the only reason it can be quoted at a flat price.

Fixed fee · one engagement

What you end up with

  • Assessment findings and the recommended architecture
  • The model running in your environment, wired into named systems
  • Validation results against your own tasks
  • A four-hour live training session for your team
  • API reference, user manuals and setup guides

Technical advisory

Ongoing technical direction under a master services agreement, for companies where AI has become part of how they operate and someone needs to be accountable for the decisions. Scope is set per statement of work, so it never quietly becomes open-ended.

Day rate · 12-month term

What you end up with

  • An AI roadmap that gets revised as things change
  • Platform and API selection, with the trade-offs written down
  • Application architecture design and technical review
  • Performance monitoring and optimisation
  • A quarterly business review, on the record

Security & compliance review

A review of the implementation itself: how data moves, where it rests, who can reach it, and what happens to it when the engagement ends. Included in every deployment; available on its own if you already have something running and want a second pair of eyes.

Included in deployment · standalone per SOW

What you end up with

  • Encryption review — in transit and at rest
  • Data pipeline audit and handling guidance
  • Compliance assessment against your regulatory position
  • Privacy guidance for the data the model touches
  • Written confirmation of secure destruction on exit
How it works

Five steps. Each one leaves a document behind.

If a stage did not produce something you can read afterwards, it did not really happen. That is how projects end up impossible to hand over.

Assess

We look at what you actually run: systems, data, integrations, constraints, and the people who will end up using this.

You get

A findings memo and the recommended architecture — including the options we rejected, and why.

Design

Model, hosting, integration points, data flow, success criteria and schedule — all decided on paper before anything is touched.

You get

A deployment plan naming the systems, the model, and the tests it has to pass.

Install

The model is deployed and configured in your environment and connected to the workflows named in the plan. No surprises, because the plan is the contract.

You get

A running system, plus its configuration and access record.

Test & train

Validated against the criteria set in step two, tuned, then handed to the people who will use it in a four-hour live session.

You get

Validation results, the API reference, user manuals and setup guides.

Keep it current

Under advisory, it keeps getting revised: monitoring, tuning, platform changes, and a plain recommendation about what to do next.

You get

A quarterly business review and a written record of what changed.

Terms

The terms are the reason a first project here is low risk.

We are asking you to hire a small firm you have not worked with. The honest way to make that easier is not a testimonial page — it is terms that put the risk on our side of the table. These are all in the agreement.

50 / 50
Payment
Half on signature, half on delivery. No retainer held, no prepaid block of hours to burn down.
$200
Expense ceiling
A hard cap on out-of-pocket expenses for a deployment. Anything over it is ours, not an invoice you did not expect.
4 hours
Training, included
A live session with the people who will actually use the system. Not a recorded course, and not an upsell.
You own it
Deliverables & IP
Everything we make for you is yours. We keep only our own pre-existing tools and methods — never your configuration, data or documentation.
Net 30
Advisory invoicing
Monthly, in arrears, against work recorded on a statement of work. Platform and API subscriptions are billed to you directly at cost, never marked up through us.
On exit
Your data
Securely destroyed when the engagement ends, confirmed in writing — not left sitting in an account nobody owns any more.
Pricing

Priced by how much ground there is to cover.

Every engagement is set out in a written agreement — scope, deliverables, timeline, price — before work begins.

Start here

Deployment sprint

$3,000fixed

One system, one model, one defined use. The project that tells you whether this works in your business before anyone commits to more.

  • Assessment, deployment, integration and testing
  • Four-hour live staff training
  • Full documentation you keep
  • 50% on signature, 50% on delivery
  • Out-of-pocket expenses capped at $200
  • Changes are quoted, never absorbed silently
Scope a sprint

The ongoing engagement

Advisory retainer

$500per day

Ongoing technical direction under a master services agreement, for companies that have decided AI is now part of how they operate.

  • Strategy, roadmap, platform and API selection
  • Architecture design and technical review
  • Data pipeline design; security and compliance review
  • Quarterly business reviews, on the record
  • 12-month initial term, annual renewal
  • Monthly invoicing, net 30 · scope set per SOW
Talk about a retainer

Quoted, not listed

Custom programme

Per SOW

Several systems, a regulated environment, or a deadline that has to be met. Priced against what the assessment finds rather than against a rate card.

  • Custom development at a fixed price per statement of work
  • Multi-system integration and phased delivery
  • Compliance-led work with documented controls
  • A fixed schedule with milestones you can hold us to
  • Runs alongside an advisory retainer
Request a quote

Platform and API subscriptions — the model provider, the cloud account — are billed to you directly at cost and never marked up through us. If the honest answer to your problem is a $40-a-month off-the-shelf tool, we will tell you that instead of quoting you.

Who you would be working with

REPLACE — photograph of the person doing the work, square crop.

[ FOUNDER NAME ]

Principal · OmniCognit LLC

REPLACE — two or three sentences, first person. Where you worked before this, what you built there, and why you started taking this work on directly. Someone spending $3,000 with a small firm they have never worked with is not buying a company; they are buying one named person's judgement. Say who that is.

  • REPLACE — previous role and employer, with dates
  • REPLACE — a system you built and what it did in production
  • REPLACE — a certification, degree or published work that can be checked

REPLACE — LinkedIn profile

Note to the owner: this is the only unverified block on the page — every commercial term stated elsewhere comes straight from your signed agreement. With no case studies and no client logos yet, a named face with a checkable history is the single highest-value thing you can add here. Fill it in before pointing the domain at this page.

Questions

The six questions that actually decide this.

If any answer below is not good enough, better that we both find out now than after a contract.

Which model do you use?

Whichever one survives testing against your tasks. Model selection is part of the work, not a house preference resold to everyone — the field moves too fast for a fixed answer to stay right for long. You get the shortlist, the evaluation results and the reasoning.

Do we need to buy GPUs?

Almost certainly not, and we will say so plainly if the assessment disagrees. Most businesses this size are best served by a hosted model with the integration work done properly around it. Selling infrastructure is not in scope here, which is exactly why the recommendation is worth something.

What happens if it does not work?

What “works” means is agreed in step two, in your language, and written into the plan before installation. If validation does not meet it, that is ours to resolve inside the fixed scope — not a change order. This is the reason the scope is drawn so tightly at the start.

What do you need from us?

Access to the systems named in the plan, one person internally who can answer questions and make decisions, and a real task to test against rather than a hypothetical one. The training session needs the people who will actually use the system in the room, not only their managers.

Why is a deployment only $3,000?

Because it is deliberately one system, one model, one defined use — small enough to hold to a fixed price without padding it. Work spanning several systems or a regulated environment is quoted against the assessment and costs considerably more. The sprint is priced to be a decision you can make quickly, not a discount on something bigger.

How long does it take?

The schedule is set in step two, once we know what we are connecting to, and it goes in the agreement. We would rather give you a date we can hold than a fast one we cannot — and if the assessment shows the thing you want is not buildable at this budget, you will hear that in week one rather than month three.

Get in touch

Tell us what you run. We will tell you what is buildable.

This is not a discovery call in disguise. You will get back either a scope and a price, or a straight explanation of why this is not a fit. Both are useful, and the second one is free.

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