Services / Secure AI Transformation

Adopt AI without creating security debt.

Most AI transformation ends at a slide deck or a pilot you can’t own. Ours ends at shipped software, secure by default, governed, and yours. Same shape the big firms sell. At a scale you can actually use.

✓ Shipped pilot in 60–90 days ✓ Secure by default ✓ You own it, no lock-in
The approach

Discover, govern, build, operate.

AI adoption is already happening, the question is whether it’s governed. We inventory your AI usage, implement governance, ship one secure pilot, test AI-specific risks, and produce the evidence customers, auditors, and executives need to trust it.

01

Discover

Inventory AI usage, tools, vendors, copilots, and data flows, including shadow AI, and the business value behind each.

02

Govern

Set policy, risk tiers, a use-case approval path, vendor and model review, and the evidence plan auditors will ask for.

03

Build

Ship one secure AI workflow with access controls, human-in-the-loop, logging, evals, and a rollback path.

04

Operate

Monitor usage, failures, cost, abuse, and drift, and keep the evidence pack current as the system changes.

What you walk away with

AI use-case inventory
Known and shadow AI, owners, systems and data touched, value, and risk.
AI risk register
Ranked risks across data, identity, vendors, models, agents, and prompts.
Acceptable-use policy
Clear rules for employees, engineers, vendors, and customer data.
Use-case approval workflow
Lightweight intake for new AI tools, automations, and product features.
Secure pilot
One production-safe workflow with controls, logging, evals, and rollback.
Evidence pack
Board-, customer-, auditor-, and procurement-ready proof.
What drives the cost

Why we scope the build instead of flat-pricing it.

A 5-person startup adding one AI feature and a regulated company rewiring ten systems are not the same project. We’d rather show you the levers than quote you a fake-precise number.

Systems & integrations

How many places the AI has to touch, one app or a tangle of internal tools.

Data sensitivity & compliance

Regulated or sensitive data means more governance, controls, and review.

AI complexity

A single assisted feature vs. a multi-agent, tool-using system with real autonomy.

Org size & maturity

Your existing stack, data hygiene, and how much process already exists.

Your team’s capacity

How much you can take on in-house vs. what we carry, this lowers cost fast.

Build vs. advisory

How much is us shipping code vs. guiding your team to ship it.

Secure & governed by default

Security isn’t a later phase.

Because we’re a security company first, your AI build comes with the things most transformation projects skip until something breaks.

Data & access design

What the model can see and do, scoped from day one, not retrofitted.

AI red teaming

Prompt injection and tool-abuse testing via DeepExploit before it ships.

Monitoring & guardrails

Visibility into what your AI is actually doing in production.

Governance documentation

The paper trail your auditors and customers will ask for.

You own everything.

The code, the models, the infrastructure, the documentation, all yours. No-lock-in is a deliberate principle. If you want to take it in-house or move it elsewhere, nothing about how we work stops you.

strategy → shipped
secure by default
no lock-in
FAQ

Common questions.

How is this different from a big consulting firm’s AI transformation?

Same shape (strategy, roadmap, build, govern) at a scale a lean company can actually use, with security native rather than bolted on. The big firms end at a slide deck or a pilot you don’t own. We end at shipped software you own, secured by default.

What does it cost?

The Discovery starts at $5,000, a bounded, fixed-scope engagement whose job is to size the real build. We don’t publish a fixed build price because org size and operational complexity move it a lot; instead we scope it during Discovery and show you exactly what drives the number. Build work typically runs from $12,000/week, but that’s a starting point, not a flat rate.

What actually drives the cost?

How many systems and integrations the AI touches, how sensitive your data is and what compliance scope applies, how complex the AI itself is (a single feature vs. a multi-agent, tool-using system), your org size, and how much your own team can take on. Discovery prices the build against these, so you get a real number tied to your situation, not a guess.

Will we be locked into you?

No. You own the code, the models, the infrastructure, and the documentation. No-lock-in is a deliberate principle, if you want to take it in-house or to another team, you can.

How do you avoid “PowerPoint transformation”?

Every engagement ends in working software, not slides. The Discovery produces a plan that names a shippable pilot; the build sprint ships it. If there’s nothing running at the end, we haven’t done our job.

Start with a discovery, not a slide deck.

A bounded, fixed-scope discovery that ends in a plan, a named pilot, and a real build quote tied to your situation.