AI & IT Solutions
Build the product around the model, not just the model.
Seaggle builds the interfaces, services, and integrations that turn a capable model into something people actually use — with the review paths, permissions, and reliability that production demands.
When this fits
Signals that this is the right conversation
A model with no interface changes nothing. The value shows up in the workflow around it: how a person reviews an uncertain answer, how an approval is captured, how the result reaches the system of record, and how the whole thing behaves when a dependency is slow. That surrounding engineering is usually larger than the model work and is routinely underestimated.
- A model or API works and there is no usable way for people to work with it
- AI output needs to reach an existing system of record reliably and idempotently
- Review, approval, and audit workflows need to exist before anyone will trust automation
- An internal tool has outgrown spreadsheets and manual handoffs
- Delivery capacity, not clarity, is the constraint on your roadmap
What Seaggle delivers
Deliverables, arranged by when they arrive
Each of these is an artifact you receive and can use without us in the room.
Design
- Workflow design around the model, including the uncertain and failure cases
- Interface design for review, correction, and approval as first-class tasks
- API and integration contracts with versioning and clear error semantics
- Architecture decision records for the choices that will be questioned later
Build
- Web and internal applications with authentication and role-based access
- Services and APIs with streaming, timeouts, retries, and graceful degradation
- Integrations into ERP, CRM, ticketing, and document systems — idempotent and reconcilable
- Automated tests weighted toward fast unit and contract coverage
Operate
- Observability across the user journey, not only the model call
- CI/CD with reversible releases and feature flags
- Documentation, runbooks, and onboarding for the operating team
- Handover with deliberate pairing so capability transfers
Solution patterns
Shapes this work commonly takes
These are patterns rather than products. Select one to see how it works, where a person stays in the loop, and what we design against.
Human-in-the-loop review interface
Automated output needs a person's judgement before it is acted on.
- How it works
- A queue prioritised by confidence and impact, side-by-side evidence and source, one-click accept or correct, and every correction captured as evaluation data.
- Human checkpoint
- The interface is the checkpoint — reviewing is the job it is designed for.
- Risks we design against
- Rubber-stamping under volume pressure. Countered by surfacing evidence well, sampling for audit, and measuring reviewer agreement.
System-of-record integration
An approved result must reliably update a core business system.
- How it works
- Idempotent writes with correlation identifiers, an outbox for delivery guarantees, reconciliation against the target system, and dead-letter handling with alerting.
- Human checkpoint
- Reconciliation exceptions surface to an owner rather than silently accumulating.
- Risks we design against
- Duplicate or partial writes during retries. Prevented by idempotency keys and reconciliation rather than by hoping.
Internal operations platform
A critical process runs on spreadsheets, shared inboxes, and tribal knowledge.
- How it works
- Model the domain, build the workflow with proper state and permissions, and integrate the systems it touches — with the automation added where it earns its place rather than everywhere.
- Human checkpoint
- State transitions that matter are explicit, attributable, and auditable.
- Risks we design against
- Automating a broken process. Avoided by mapping and improving the process before encoding it in software.
Representative workflow
End to end, with the checkpoints visible
A worked example of how the pieces connect in production. The static sequence below is the whole content — nothing is hidden behind animation.
- 01
Map the real workflow
Including the exceptions people currently handle informally.
- 02
Design for the uncertain case
The review path is designed first, not bolted on after the happy path.
- 03
Define contracts
APIs and integration semantics agreed before implementation starts.
- 04
Build in increments
Shipped to a real user group early enough for the feedback to change things.
- 05
Integrate idempotently
Writes that can be retried safely and reconciled against the target.
- 06
Instrument the journey
Observability across the whole path, not only the model call.
- 07
Hand over
Documentation, runbooks, and deliberate pairing with your engineers.
Representative example
Evaluation & controls
What separates production work from a demonstration
A demonstration proves something can happen once. These controls are how you know it keeps happening correctly.
Designed failure behaviour
Timeouts, retries, and degradation are designed decisions. What the user sees when the model is slow or unavailable is specified rather than discovered in an incident.
Idempotent integration
Writes to systems of record carry correlation identifiers and are safe to retry, with reconciliation to catch what still slips.
Role-based access
Permissions enforced server-side and aligned to your identity provider, so what a user can see in the product matches what they may see in the source systems.
Auditable state changes
Who approved what, when, and on what evidence — recorded, because that is the question asked after something goes wrong.
Reversible releases
Feature flags, canaries, and one-command rollback, so shipping is routine rather than an event requiring a change board.
Accessibility as a requirement
Internal tools are used all day by people with a range of needs. WCAG conformance is part of done, not a later remediation project.
Technology we work with
Named to explain the work rather than to imply endorsement. Tool choices follow the requirement, and we work with what you already run wherever that is sensible.
- TypeScript
- React / Next.js
- Node.js
- Python / FastAPI
- Go
- PostgreSQL
- Redis
- Kafka
- OpenAPI
- Playwright
Getting started
Where a first engagement begins
A discovery and design engagement producing the workflow, interface direction, and integration contracts — followed by delivery in two-week increments against a backlog you prioritise.
Discuss a buildQuestions
Can you work alongside our engineers?
That is the arrangement we prefer. Shared repository, shared standards, shared review, with deliberate pairing so capability transfers to your team rather than concentrating in ours.
How do you price delivery?
Discovery is fixed price. Delivery is priced per squad sprint, because fixed-bid software either pads the estimate or fights every change request. You can stop at a sprint boundary with working software in hand.
What happens to the code afterwards?
It is in your repository from the first commit. We finish with a handover pack, an architecture walkthrough, and a support window for your team's questions.
Discuss a build
Bring the problem, the current environment, and what better should look like. We will tell you what is realistic before anyone signs anything.