Your AI project,
live in weeks.
The hard part was never the model.
We have watched the same three failures across every AI program we have been called into. All three are engineering problems, and all three are solvable in weeks — by people who have shipped it before.
The demo works. Production doesn't.
A notebook and a happy path are not a system. Error handling, retries, rate limits, evaluation, cost control, and the ugly edges of real data are where the schedule disappears.
Security review stops it cold.
The pilot reaches the CISO with no access model, no audit trail, and no answer for where the data goes. The project does not get rejected — it gets deferred, indefinitely.
Nobody owns the last 20%.
Deployment, monitoring, the admin screen someone has to use every day, the runbook. The work that turns a prototype into something a team can actually operate.
Who we work with
Founders and product teams
You need a vertical slice live in production, not a slide deck — and you need it before the next board meeting.
Engineering leaders
Your team can build it, but not this quarter. We deliver the first version and hand it over in a state they will respect.
Regulated enterprises
Healthcare, financial services, and government, where the deployment model and audit trail decide the project before the demo does.
Every layer, one team.
From GPU provisioning to the button a user clicks. No handoffs between an infrastructure vendor, a backend contractor, and a design shop.
Agents that do the work
Systems that browse, read documents, call your APIs, write files, and finish a task end to end — with the tool layer, retries, and evaluation that keep them reliable.
Model serving & GPU infrastructure
vLLM deployments, quantization, batching, and routing across providers and self-hosted models. Sized to your workload instead of your vendor's pricing page.
The data and integration layer
Connecting the systems the work actually lives in — ERP, CRM, EHR, ticketing, internal APIs, document stores — with auth, pagination, and rate limits handled properly.
The application around it
The chat surface, the admin dashboard, the review queue, the report someone opens on Monday. A model with no interface is not a product.
Access control and audit
Role-based permissions, per-action audit logging, and data-protection controls wired into the runtime — so the security review is a conversation, not a wall.
A handoff your team can run
The repository, deployment notes, and a working session with your engineers. You should be able to extend what we built without calling us.
Four steps. No open-ended retainer.
Every stage has a defined output. If we are not adding value, the engagement ends on schedule and you keep everything we built.
Discover
A short working session to lock scope, success criteria, integrations, and who owns API keys and data access.
You get
A written scope with a cap, a timeline, and a fixed quote.
Build
Focused implementation on your infrastructure. You see working software as it lands, not a status deck.
You get
Running software in your environment, in your repository.
Review
A walkthrough against the acceptance criteria we agreed in discovery. We tighten the edges and document what shipped.
You get
Signed-off acceptance and a record of what was built.
Handoff
Repository access, deployment notes, and a working session with your engineers so they can extend it without us.
You get
Your team owns and operates the result.
Time-boxed, with a written scope cap.
We quote from your backlog after a short discovery call, so the price reflects your integrations and compliance needs rather than a guess. You get a written proposal before any work starts.
Sprint
2 weeksOne production-ready vertical slice. A single core flow, live in your environment.
Included
- One primary user journey, end to end
- One or two integrations per written agreement
- Authentication and onboarding when in scope
- Logging and health checks appropriate to the slice
- Handoff documentation and a working session
MVP
4–6 weeksA broader product slice — multiple flows, more integrations, and room for one iteration cycle.
Included
- Multiple flows from a backlog capped in writing
- Expanded integrations and background jobs
- Admin or internal tooling when in scope
- RBAC, audit, and data-protection patterns applied
- Same handoff rigor as Sprint, more surface area
Enterprise program
8+ weeksMulti-month engagements: GPU clusters, org-wide rollout, and compliance-heavy delivery.
Included
- Infrastructure audit and architecture blueprint
- Production deployment across environments
- Security hardening and SSO integration
- Team training and embedded engineering
- Retained support and capacity planning
Not sure which fits? Start with the shortest one — we will tell you on the call if you need more. See the full consulting scope.
We are not an agency that discovered AI.
We are the engineering team behind a production AI platform. When we build for you, you get the stack we already trust with our own product.
We build on what we ship
Aureum is a production agent platform we built and operate ourselves — the same runtime, patterns, and failure modes we bring to your project. Consulting firms learn this on your budget. We already paid for it.
Full stack, single team
GPU provisioning through React components, owned by one team. No triage between an infrastructure vendor, a backend contractor, and a design shop while your timeline slips.
No vendor lock-in by design
We build across providers and self-hosted models. If your board decides next quarter that data cannot leave the building, that is a configuration change, not a rewrite.
Governance is not phase two
Access control, audit logging, and data protection go in while we build. It is the difference between a pilot that reaches production and one that dies in security review.
The platform behind the work
Your build can start from it, extend it, or ignore it entirely — the choice is yours.
The things people ask before signing.
Who owns the code and the IP?
You do, under the terms of your statement of work. We walk through IP, licensing, and any third-party services on the intake call before anything is signed.
Why don't you publish fixed prices?
Because the honest number depends on your integrations, your data, and your compliance requirements. We quote from your backlog after a short discovery call, and you get a written proposal before work starts. No hourly meter running in the background.
Where does our data go?
Wherever you require. We deploy into your AWS, Azure, or GCP account, or fully on-premise for air-gapped environments. We build across model providers and self-hosted models, so restricting where inference runs is a configuration decision, not a rewrite.
What if the scope changes mid-build?
Scope is capped in writing at the start. Changes go through change control — we tell you the cost and timeline impact before we do the work, not after. That is the entire point of a time-boxed engagement.
Do we have to use the Aureum platform?
No. Starting from our platform is usually faster, but plenty of engagements are built on your existing stack. We will recommend whichever gets you to production sooner and say so plainly if that is not our product.
What happens after the engagement ends?
You operate what we shipped. Extend it with your own team, or bring us back for follow-on work. There is no dependency built in by design and no retainer you have to cancel.
Let's talk about what you're building.
Tell us where you are and what needs to be live. We will confirm fit, timeline, and the right shape of engagement — before anything is signed.
For Investors
Interested in our seed round? We would love to share our vision for the future of enterprise AI security.
invest@aureumintelligence.com →