Full Stack → Tested → Handed Off. Production-grade software in weeks, not quarters.
Python/FastAPI backend, Next.js/TypeScript frontend, PostgreSQL with Alembic migrations. We build the entire stack — auth, storage, API, and dashboard — with 80%+ test coverage and documentation your team can maintain.
For PropTech, LegalTech, and FinTech products where audit trails, role-gated actions, PDF certificate generation, and reversible workflows are not optional. We design the compliance layer from day one.
Stripe checkout sessions, idempotent webhook processing, credit ledgers, organization wallets, and promo codes — wired correctly so edge cases do not become billing incidents at 2am.
Async AI generation pipelines built on domain events, not inline API calls. Content orchestration services, versioned prompt registries, and feature flags for safe rollouts. AI failures never break your core product.
Database schema, service boundaries, API contracts, feature flags, and a written SSOT document — all designed before line one of code. Clients who engage us for architecture avoid the refactors that cost 3x later.
What We Build → Full Stack → Handed Off. Production-grade software in weeks, not quarters.
Python/FastAPI backend, Next.js/TypeScript frontend, PostgreSQL with Alembic migrations. We build the entire stack — auth, storage, API, and dashboard — with 80%+ test coverage and documentation your team can maintain.
For PropTech, LegalTech, and FinTech products where audit trails, role-gated actions, PDF certificate generation, and reversible workflows are not optional. We design the compliance layer from day one.
Stripe checkout sessions, idempotent webhook processing, credit ledgers, organization wallets, and promo codes — wired correctly so edge cases do not become billing incidents at 2am.
Async AI generation pipelines built on domain events, not inline API calls. Content orchestration services, versioned prompt registries, and feature flags for safe rollouts. AI failures never break your core product.
Playbooks, QA loops, and ownership transfer so your team can run it without us.
From database schema to payment integration to AI pipeline — SeaTechOne ships production-grade software for founders and operators who need a technical partner, not another consultant.
A real product. In production. Built end to end.
Multi-tenant SaaS for real estate agents. Stripe billing, AI staging pipeline, MLS compliance certificate generation, and role-gated publication workflows — built from scratch.
Organizations, members, and role-gated actions. Stripe checkout sessions, credit ledgers, and idempotent webhook processing. Async AI staging pipeline that never blocks a request handler.
Full audit trail on every staging job. PDF compliance certificates generated on approval. Reversible publication workflow with role-gated sign-off — designed for MLS submission requirements.
Short, clear write-ups from real projects — what worked, what didn't, and why.
When we started building SEAREI, the first decision was scope: build a demo or build a product. We built a product.
That meant multi-tenancy from schema design, not bolted on later. Every table carries an org_id foreign key. Row-level queries are scoped at the repository layer — no controller can accidentally leak cross-tenant data. This isn't a policy; it's enforced structurally.
FastAPI on the backend, Next.js 14 on the front, PostgreSQL with Alembic migrations, Redis for job queues, and Stripe for billing. The AI pipeline runs as a background worker — separate process, separate failure domain.
We wrote the architecture document before a single line of application code. Service boundaries, API contracts, data model, feature flags, environment config — all documented in a living SSOT. Every engineer on the project reads it first.
org_id; no raw queries bypass the scope check.MLS compliance certificates are generated from the audit log, not from live state. That means the certificate reflects exactly what existed at the time of the transaction — immutable, exportable, signed.
Result: a codebase where you can add a new tenant tier, a new compliance rule, or a new AI provider without touching the core request path.
AI image generation is slow. A virtual staging render can take 8–25 seconds. That's an eternity inside a synchronous HTTP request.
The naive solution is to just await the AI call. It works in demos. In production, it ties up a worker process, kills your p95 latency, and falls apart under any real load.
complete.complete, the UI fetches the finished image.Compliance certificate generation is a different kind of slow — it walks the audit log, assembles records, renders a signed PDF. Same pattern: enqueue, worker processes, status poll, download link. No request handler waits.
Rule: if it takes more than 300ms, it belongs in a worker.
Most products add compliance features after a customer asks for them. By then, the database isn't ready and you're retrofitting audit trails onto a schema that was never designed to support them.
We designed SEAREI's data model around compliance from the start — not because we had auditors breathing down our necks, but because we knew the product would eventually need to prove what happened, when, and to what data.
created_at — immutable timestamp, set on insert, never updatedupdated_at — auto-updated on every writecreated_by — user ID of the actor who created the recordupdated_by — user ID of the last actor to modify itCompliance-relevant records are never hard-deleted. A deleted_at timestamp flags them as inactive; the data stays in the table. A separate audit_log records every state transition with a before/after JSON diff, timestamp, and actor ID.
When a user requests a compliance certificate, the system walks the audit trail for a given property or transaction, assembles the relevant records, and renders a signed PDF. No manual data collection. No screenshots. No spreadsheet exports. The certificate reflects exactly what the audit log shows — immutable and exportable.
Not every user can publish a compliance record. Role checks live at the repository layer, not the controller. A user without the compliance:publish permission gets a 403 before any data is touched.
Takeaway: designing for audit upfront is cheaper than retrofitting it. It also changes how you think about deletes, updates, and state — and those decisions compound across the whole architecture.
We work in fixed-scope phases. Each phase has a written spec, defined deliverables, and a clear budget before we write a line of code. No open-ended retainers with unclear output.
A shippable v1 with auth, core workflow, and payments typically takes 8 to 12 weeks. Compliance layers, multi-tenant orgs, or AI pipelines add 4 to 8 weeks. We scope this in writing before we start — no surprises mid-build.
Both. We prefer greenfield products where we design the architecture from scratch — schema, service boundaries, API contracts, the full stack. We also take on brownfield work when the existing codebase is well-structured. We will tell you honestly if it is not.
Python + FastAPI + SQLAlchemy + Alembic on the backend. Next.js 15 + React + TypeScript on the frontend. PostgreSQL in production, Stripe for payments, S3-compatible storage. Redis for async job queues. Tools your team can maintain and extend after handoff.
Yes. SEAREI — our own product — generates MLS compliance certificates, maintains full audit trails, and uses role-gated publication workflows. PropTech, LegalTech, FinTech, and HealthTech are where we do our best work. Compliance is designed in from day one, not bolted on later.
Via async job queues, not inline API calls. The request handler validates input and enqueues a job — then returns immediately. A background worker calls the AI provider, writes the result, and updates job state. The UI polls a lightweight status endpoint.
This means AI generation failures never block your users, never tie up server workers, and are always retryable. The same pattern handles any slow, compute-heavy task — PDF generation, batch processing, report rendering.
All source code in a private repo you own. Written architecture documentation covering schema, service boundaries, API contracts, and feature flags. Test suite with 80%+ coverage. Reversible Alembic migrations. Deployment runbook. Incident runbook. 30-day support window after launch.
You should be able to hire any competent engineer and have them productive in the codebase within a day. That is our standard.
You do. Everything we build for your engagement — code, architecture docs, design assets — transfers to you on final payment. We retain no license to your product or its codebase.
Fixed-scope phases with a written spec and clear deliverables for each. No hourly billing. You know exactly what you are getting and what it costs before we start. Phase budgets typically range from $15,000 to $45,000 depending on scope and complexity.
Yes. Monthly retainer engagements are available after the build. Retainers cover new feature phases, dependency upgrades, incident response, and architecture reviews. Most clients stay on retainer after launch.
Start a Project
Tell us what you're building, where you are in the process, and what's blocking you. We respond within one business day with a clear next step — usually a 45-minute architecture conversation.
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