DesignKompanie

AI application development

Production AI software, not demo wrappers.

We engineer resilient AI applications that solve real operational bottlenecks. Production LLM pipelines, pgvector semantic search, streaming user interfaces, and deterministic data validation.

Claude APIOpenAIpgvectorNext.js 15TypeScriptPostgreSQL
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AI application development architecture

N° 01Engineering philosophy

Beyond the wrapper. Deterministic logic meets AI

Most AI applications fail in production because they treat LLMs as magical databases. When a prompt changes, output quality breaks, latency spikes, and token costs explode. Production AI requires a rigorous software engineering foundation.

We design AI applications where probabilistic language models handle unstructured inputs (emails, documents, images, voice), while strict deterministic code handles business logic, financial math, validation, and database state. The result is software that feels intelligent to users while remaining 100% reliable and auditable.

N° 02Production AI pipeline

Architecture built for enterprise reliability

01

Structured Outputs & Validation

Strict JSON schema enforcement with Zod and TypeScript. Model outputs are validated before hitting your database; invalid responses automatically retry with error feedback.

02

Hybrid Search & pgvector

Retrieval-Augmented Generation (RAG) using PostgreSQL pgvector. Combines semantic vector similarity with full-text keyword search and tenant-isolated metadata filters.

03

Model Routing & Cost Control

Tiered multi-model architecture: fast, inexpensive models (Claude 3.5 Haiku, GPT-4o-mini) handle routine classification, escalating to flagship reasoning models only when confidence drops.

04

Continuous Evaluation & Evals

Human corrections and approved outputs automatically feed back into private evaluation test suites. Your AI application compounds in accuracy on your real customer data over time.

N° 03Data privacy & isolation

Zero training data leakage. Tenant-isolated privacy

Enterprise clients will not adopt AI tools that expose their proprietary trade secrets. We enforce strict multi-tenant data boundaries at the database layer using PostgreSQL Row Level Security (RLS).

All API integrations use enterprise zero-data-retention agreements where your customer data is never used by model providers for training. Everything remains within your private VPC or cloud perimeter.

N° 04Streaming UX

Instant visual feedback. Sub-second perceived latency

Nothing kills user engagement like a blank screen with a spinning loader for 15 seconds. We build real-time streaming interfaces using Server-Sent Events (SSE) and Vercel AI SDK.

Users see thinking tokens, preliminary extractions, and incremental updates stream across the screen immediately, transforming heavy computation into an intuitive, transparent experience.

Selected work

Shipped, not theorised.

LaycanDesk AI maritime chartering application interface
LaycanDesk AI product marketing platform

01

LaycanDesk

Maritime · AI chartering desk

An AI chartering desk for dry-cargo shipbroking shops. It ingests hundreds of messy cargo circulars and open-tonnage emails arriving daily in inbox streams, turns them into a structured database board, matches each stem against candidate vessels, and calculates voyage TCE economics in under 90 seconds.

Engineered with Cloudflare signed email routing, multi-tier Claude extraction, deterministic financial calculators, and tenant-isolated PostgreSQL RLS.

What we built

  • Email parsing pipeline converting unstructured plain-text circulars into structured JSON
  • Two-tier LLM extraction with cheap first pass escalating on low confidence scores
  • Human-in-the-loop correction logging that doubles as evaluation regression tests
  • Deterministic voyage revenue and bunker fuel estimator tested against manual vouchers
  • Sub-second vessel ranking across laycan dates, cargo size, gear, and sanctions data
Next.js 15TypeScriptClaude APIPostgreSQLSupabaseCloudflare WorkersTailwind CSS
Visit laycandesk.comOpen the live demo
Hauloport logistics management system
Hauloport live rate calculations

02

Hauloport

Logistics · multi-tenant SaaS

Automated logistics billing and rate comparison SaaS platform. Features dynamic carrier cost calculations, automated PDF shipping manifest rendering, and tokenized tracking systems.

What we built

  • Multi-tenant PostgreSQL with row-level security per organization
  • Automated document generation and PDF rendering
  • Stripe Connect double-entry ledger settlement
Visit hauloport.comOpen the product demo

Investment

Fixed scope. No drift.

From $24,000 — production AI application build.

  • End-to-end system architecture & model selection matrix
  • Prompt engineering, system instruction design & evaluation dataset
  • PostgreSQL pgvector embeddings & hybrid semantic search pipeline
  • Zod schema validation & deterministic error interception
  • Real-time streaming UI with Server-Sent Events (SSE)
  • Admin observability dashboard with token cost & latency metrics
  • 30-day post-launch warranty and model drift monitoring
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Questions

The answers we give most often.

What AI models and providers do you work with?
We work primarily with Anthropic (Claude 3.5 Sonnet / Haiku) and OpenAI (GPT-4o / GPT-4o-mini), as well as open-weights models (Llama 3, Mistral) hosted privately on AWS Bedrock, Together AI, or Cloudflare Workers AI.
How do you prevent hallucinations in business software?
By bounding the model's domain with strict system prompts, grounded Retrieval-Augmented Generation (RAG) referencing verified documents, and hard deterministic validators. If a model output fails schema validation or contains unsupported values, the system intercepts it before the user ever sees it.
How do you keep token costs from getting out of hand?
We implement prompt caching, prompt compression, intelligent model routing, and client-side rate limiting. In our production builds, over 80% of routine queries are resolved by high-speed, low-cost sub-models or cache hits, reducing monthly inference bills by up to 75%.
Can you build AI agents that take autonomous actions?
Yes. We build multi-step tool-use agents equipped with database query capabilities, external API webhooks, document generation, and email drafting. For high-stakes workflows (such as moving money or signing contracts), we enforce human-in-the-loop approval gates.
How much does an AI application development project cost?
Production AI MVPs start at $24,000 for focused data extraction, intelligent search, or domain-specific copilot applications. Complex enterprise multi-agent platforms start at $45,000.
Do we own the prompts, fine-tuning data, and code?
Yes, 100%. All custom prompt libraries, evaluation datasets, pipeline code, and vector database schemas belong exclusively to you under full IP assignment.

Start here

Tell us about your AI software concept.

The data inputs, the target workflow, and the operational outcome you want to unlock. We will respond with an architectural blueprint, model selection strategy, and fixed quote.

Or email hello@designkompanie.com

Reply within two business days.

Related services

SaaS developmentMVP development servicesNext.js developmentB2B SaaS development

Next step

Turn your AI concept into a working business.

Tell us about the problem and your data. We'll show you how we'd architect it.

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AI Application Development: Production LLM Apps