A team with a business owner
Your operational expert and technical owner work with our engineers and architecture and delivery specialists. We agree the team around the scope and keep decisions close to the people using the system.
Engineers inside your business.
Forward-deployed engineering brings business understanding and hands-on delivery into one team. We embed with yours to turn AI opportunities into working systems and lasting capability.
Built around the work.
For business and technology leaders who have access to AI tools and need help making them useful in daily operations.
One workflow to start
Examples include assisted customer operations, internal knowledge retrieval, document preparation and engineering workflows. We validate fit during discovery before committing to a build.
A wider operating capability
The first deployment creates reusable integrations, evaluations and practical experience. Expand to the next workflow when its value and ownership are clear.
From opportunity to everyday use.
Understand the work
Work with the people doing the job. Map the process, data, systems and exceptions. Agree on a baseline and choose one useful workflow with a business owner.
Outputs we agree with you
- Workflow and data-access map
- Baseline for time, cost and quality
- Prioritised opportunities and a scoped build plan
Build with your team
Engineers and domain experts work together in a shared delivery loop. Connect the tools you already use, test against representative examples and involve users before the workflow goes live.
Outputs we agree with you
- Working prototype and reviewed integrations
- Evaluation examples and acceptance criteria
- Shared code, documentation and decision record
Prove it in production
Set the permissions, human checkpoints, monitoring and recovery path. Release to a defined group, compare results with the baseline and decide what is ready to expand.
Outputs we agree with you
- Production release and go-live checklist
- Monitoring, escalation and rollback plan
- Measured results against the agreed baseline
Make it repeatable
Turn useful integrations and evaluation methods into capabilities your team can maintain. Train users and technical owners, then prioritise the next workflow using what the first deployment taught us.
Outputs we agree with you
- Team training and operating runbooks
- Reusable integrations and evaluation approach
- Next-workflow roadmap and support agreement
Measure the change in the work.
Agree the baseline and acceptance criteria before building. Compare the deployed workflow against them, including the cost of human review.
Time
Cycle time and manual handling per completed task.
Quality
Acceptance rate, corrections and unresolved exceptions.
Cost
Engineering, model and operating cost per useful outcome.
Adoption
Whether the intended users keep using the workflow.
Before we start.
What is a forward-deployed engineer?
An engineer who works closely with your business and technical teams to solve an operational problem. They understand the workflow, build the software and integrations, and help get it into everyday use. At MetaSvit, this is our delivery model for AI transformation.
Where should we start?
Bring a repeated task, a slow handoff or an AI pilot that has stalled. Discovery checks whether the data, access, owner and potential value are there. The first build should have a bounded scope and a measurable acceptance test.
Do we need to replace our existing systems?
We start with your current tools and data. The plan may involve integrations, changes to a workflow or targeted modernisation. The decision follows the business need and technical constraints.
Which models and platforms do you use?
We evaluate options against your workload, quality requirements, operating cost and deployment constraints. We can work with your chosen stack and document the trade-offs. Your team gets documented choices for deployment and future model changes.
Who owns the result?
We agree ownership, access and third-party licensing in the engagement. Our working approach uses a shared repository, documented decisions and a named operational owner, so your team can maintain what is delivered.
How do you handle adoption and risk?
Involve users from the prototype stage. Define the actions the agent can take, the decisions a person must approve, and how failures are handled. Training, evaluation, monitoring and recovery are part of the delivery scope. Sector-specific requirements need to be agreed with your own risk and legal owners.