AI integration should never be guesswork.
Vectrel builds custom AI systems that fit the tools, data, and teams you already have, not the other way around. Every build follows the same disciplined sequence, so you always know what happens next and who owns it.
How we work
Four decisions shape every build.
Before anyone writes code, we settle four things: what you want, whether it will work, how it gets built, and who runs it after launch. The seven phases below are how those four decisions get made.
01
Frame
Agree on the workflow, the outcome you want, and who owns what, before we propose anything.
maps to: Discovery and Proposal
02
De-risk
Check that your data can support the system, pick the right models and vendors, and decide how we will prove it works.
maps to: Design
03
Build
Build the system, wire it into your existing tools, put checks around it, and test it against the criteria you signed off on.
maps to: Build and Test
04
Operate
Ship it under the ownership terms we agreed, document it, hand it over, and set up support.
maps to: Deploy and Support
Every build follows the same sequence, at the depth the work needs.
Not every project needs all seven phases. During discovery we recommend the right shape. The agreement records the phases, the reviews, and the timing before the build begins.
Discovery
We learn your business before we propose anything.
Discovery maps the workflow, the systems and data involved, the outcome you want, and who owns what, before any solution is on the table. How deep it goes depends on what you are evaluating.
- Stakeholder interviews and workshops
- A review of your existing systems and data
- Workflow and process mapping
- Agreeing goals and what success looks like
Proposal
A detailed, phased plan before any commitment.
After discovery, the proposal lays out the recommended scope, the delivery phases, who is responsible for what, the timing, and the price. We use the review to settle open questions before any build work starts.
- Drafting the solution architecture
- Scoping phases and milestones
- Timeline and resource planning
- Pricing and proposal delivery
Design
Architecture and interfaces, mapped out before we build.
Depending on the project, design can cover the system architecture, data models, interface wireframes, or workflow diagrams. Reviews you sit in on confirm the decisions and surface anything unresolved before we start building.
- System architecture design
- Data model and schema design
- Interface wireframes and prototypes
- Technical specification
Build
Engineering, iteration, and regular check-ins.
We build the approved scope through working demos and feedback points you take part in. A dedicated Vectrel senior engineer stays accountable for the architecture for the full length of the build.
- Development in short cycles
- AI model integration and tuning
- Infrastructure and deployment setup
- Regular demos and feedback
Test
Rigorous validation before anything goes live.
We test the system against the acceptance criteria you signed off on: how it behaves on your real cases, how it holds up under load, and how it handles the edge cases. You test it yourself before go-live.
- Functional and integration testing
- Model accuracy checks on your real cases
- Performance and load testing
- Your team's own testing before go-live
Deploy
Launched under the ownership terms we agreed.
We ship it where we agreed: on your own infrastructure, alongside systems you already run, or with some parts in managed services and the split written down. Who owns the code, the data, and the running system is settled before launch.
- Production setup
- Deployment and configuration
- Team training and documentation
- Go-live monitoring
Support
Post-launch ownership and support are set before go-live.
Support can cover documentation, handover, monitoring, incident response, retraining, or scoped improvements. The support period, the response times, and who runs it after launch are written into the agreement.
- Monitoring and alerting
- Performance tuning
- Model retraining and drift correction
- Enhancements and iteration
Getting started
You commit to the build only after you can see it working.
Many clients start with a paid discovery or a single de-risking phase, then decide whether to authorize the full build once there is evidence to act on.
01
A paid first step
Start with a paid discovery or one de-risking phase. It is bounded, it is signed off, and it stands on its own, whether or not you go further.
02
A fixed proposal
Before you authorize the full build, the proposal is fixed and in writing. You decide with the scope and the price already settled, not left open.
Either way, you get a fixed proposal with deliverables, milestones, timeline, and price before you commit to the build. No number until we understand the work, then one you can plan around.
Integration without the usual tradeoffs.
Most vendors optimize for speed to shelf or recurring license revenue. We optimize for fit: a system that works with your team, your data, and your constraints.
Infrastructure fit
Generic AI tools get layered on top, even when they fight the systems and workflows you already run.
The system is shaped around your infrastructure, your data, and your constraints from the start.
Discovery before scope
Scope gets sold before the problem is clear, which creates rework and awkward change orders.
Discovery comes first, then phased delivery with clear outcomes, costs, and decision points.
Delivery visibility
Delivery stays opaque until a handoff or a surprise update lands in your inbox.
You see demos, progress, and honest tradeoff conversations throughout the build.
Direct senior access
Layers between you and the builders slow feedback and dilute the technical context.
You work directly with the senior engineer who owns the architecture and the tradeoffs.
Long-term ownership
Packages and repeatable playbooks optimize for the vendor, not for your team owning the system.
The system is built so your team can run, maintain, and evolve it after we leave.
Method as proof
We work under NDA, so we lead with method instead of logos. The discipline you can see on this page is the same discipline that runs inside every build.
Who is accountable
One senior engineer owns your build, start to finish.
A dedicated Vectrel senior engineer is assigned at kickoff and stays accountable for the architecture and the reviews you sit in on, for the full length of the build.
No staffing pyramid, and no handing you to a junior team after the sale.
We treat client engagements as confidential. Engagements run under NDA, and published work is anonymized by default; the client approves exactly what is shown. Named references are available on request once an engagement is underway.
See how this runs in a real buildStart a project
Bring us the workflow, product, or operating question.
We will identify what to validate first, outline the delivery path, and tell you candidly whether Vectrel is the right fit.
Do not include regulated, confidential, or sensitive data in the public intake. If you need an NDA or protected channel first, email hello@vectrel.ai.