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AUTOMATA ONE
Services

Capabilities

Web, mobile, UI/UX, and backend — engineered by the same team. No handoffs, no translation loss.

Frontend

Web Frontend

Production-grade interfaces that load fast and ship clean.

We build marketing sites, customer dashboards, and complex web apps with Next.js. Server rendering by default, design systems baked in, performance budgets enforced from day one.

Deliverables
  • Marketing site or product UI
  • Design system + theme tokens
  • SEO + meta + OG cards
  • Lighthouse 90+ benchmark
Stack
Next.jsTypeScriptTailwind v4shadcn/uiFramer Motion
Timeline
2–4 weeksMVP scope
How it ships
app/products/[id]/page.tsxNext.jsRSC
// React Server Component — streams in two waves so the
// hero paints fast and recommendations fill in after.
export default async function ProductPage({
  params,
}: {
  params: Promise<{ id: string }>;
}) {
  const { id } = await params;
  const product = await getProduct(id);

  return (
    <article>
      <ProductHero product={product} />
      <Suspense fallback={<RecommendationsSkeleton />}>
        <Recommendations productId={id} />
      </Suspense>
    </article>
  );
}

async function Recommendations({ productId }: { productId: string }) {
  // Streams in after the page shell is sent.
  const items = await getRecommendations(productId);
  return <RecommendationGrid items={items} />;
}
streamed78msedge
Mobile

Mobile Apps

iOS + Android from a single codebase.

Flutter as our default — one codebase, two platforms, no compromise on platform conventions. We ship to App Store and Play Store, not just to TestFlight.

Deliverables
  • Cross-platform app (iOS + Android)
  • Store-ready builds + screenshots
  • Auth, payments, push notifications
  • Crash reporting + analytics
Stack
FlutterDartFirebaseSupabaseSentry
Timeline
4–8 weeksBeta release
How it ships
lib/features/payment/payment_sheet.dartFlutterRiverpod
class PaymentSheet extends ConsumerWidget {
  const PaymentSheet({super.key, required this.amount});
  final double amount;

  @override
  Widget build(BuildContext context, WidgetRef ref) {
    final state = ref.watch(paymentProvider(amount));

    return state.when(
      data: (intent) => PaymentForm(
        intent: intent,
        onSubmit: () => ref
            .read(paymentProvider(amount).notifier)
            .confirm(),
      ),
      loading: () => const PaymentSkeleton(),
      error: (err, _) => PaymentError(
        message: err.toString(),
        onRetry: () => ref.invalidate(paymentProvider(amount)),
      ),
    );
  }
}
readyios + androidrelease
Design

UI / UX Design

Interfaces that feel like the brand, not a template.

Design is the first impression and the last interaction. We build systems that scale — shared tokens, reusable components, accessibility built in from the start.

Deliverables
  • User research + flows
  • Wireframes + interactive prototypes
  • Visual design + component library
  • Brand application + design tokens
Stack
FigmaFigJamRiveDesign tokens
Timeline
1–3 weeksPer scope
How it ships
app/styles/tokens.cssDesign tokensOKLCH
/* Design tokens — sourced from Figma, validated in CI.
   Same values flow into web, iOS, Android, and email. */
@layer tokens {
  :root {
    --color-accent: oklch(0.628 0.235 25);     /* Signal Red */
    --color-ring: oklch(0.83 0.12 187);        /* Singularity Cyan */
    --color-foreground: oklch(0.142 0.025 264);

    --radius-md: 0.625rem;
    --radius-lg: calc(var(--radius-md) * 1.4);

    --shadow-elevated: 0 12px 32px -10px
      color-mix(in srgb, var(--color-accent) 28%, transparent);

    /* Type scale — 1.25 ratio, 16px base */
    --text-sm: 0.875rem;
    --text-base: 1rem;
    --text-2xl: 1.563rem;
    --text-5xl: 3.052rem;
  }
}
syncedfrom Figmaall platforms
Backend

Backend & APIs

Type-safe APIs, transactional integrity, multi-region deploy.

FastAPI + PostgreSQL by default — fast iteration, strong types, predictable performance. We handle auth, payments, queues, and real-time with patterns we've shipped before.

Deliverables
  • REST or gRPC APIs
  • Database schema + migrations
  • Auth + RBAC
  • Payment integration (Stripe / SSL)
  • Multi-region production deploy
Stack
FastAPIPostgreSQLRedisResendDocker
Timeline
3–6 weeksMVP scope
How it ships
api/orders/route.pyFastAPIPostgres
@app.post("/orders", response_model=OrderResponse, status_code=201)
async def create_order(
    payload: CreateOrderRequest,
    db: AsyncSession = Depends(get_db),
    user: User = Depends(current_user),
) -> Order:
    # All-or-nothing — order + audit event commit together
    async with db.begin():
        order = Order(
            user_id=user.id,
            cart_id=payload.cart_id,
            amount=payload.amount,
            status=OrderStatus.PENDING,
        )
        db.add(order)
        await db.flush()

        await db.execute(
            insert(OrderEvent).values(
                order_id=order.id,
                type=EventType.CREATED,
            )
        )

    await queue.enqueue("order.charge", order_id=order.id)
    return order
201 created44msprod
AI

AI Intelligence

Grounded retrieval, streaming inference, eval-tested.

We ship retrieval-augmented systems that answer from your data — not from training-set hallucinations. Streaming responses, vector search, evaluation harnesses — every endpoint observable from token to cost.

Deliverables
  • Retrieval-augmented Q&A on your data
  • Streaming LLM endpoints
  • Vector search + embeddings pipeline
  • Eval harness + token telemetry
Stack
FastAPIpgvectorOpenAILangChainPydantic
Timeline
4–8 weeksMVP scope
How it ships
api/ai/answer.pyFastAPIRAG
@app.post("/ai/answer")
async def answer(
    payload: AnswerRequest,
    db: AsyncSession = Depends(get_db),
    user: User = Depends(current_user),
) -> StreamingResponse:
    # 1. Embed the question, retrieve top-k similar docs
    query_vec = await embed(payload.question)
    docs = await db.execute(
        select(Document)
        .where(Document.org_id == user.org_id)
        .order_by(Document.embedding.cosine_distance(query_vec))
        .limit(4)
    )
    context = [d.content for d in docs.scalars()]

    # 2. Stream the answer back, token by token
    async def stream() -> AsyncIterator[bytes]:
        async with llm.stream(
            system=ANSWER_PROMPT,
            messages=[
                {"role": "user", "content": payload.question},
                {"role": "system", "content": "\n\n".join(context)},
            ],
        ) as response:
            async for token in response:
                yield token.encode()

    return StreamingResponse(stream(), media_type="text/event-stream")
streaming60ms first tokenprod

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