AI Feature Sprint
One AI feature, properly built,
in 2–4 weeks. Fixed price.
Search that finds the right answer. A chatbot that doesn't make stuff up. A summary that's actually useful.
Smart Search
Search that understands what users mean — not just what they typed. Finds the right answer even when wording differs.
pgvector · Cohere Reranker · BM25
Document QA / Chat-with-PDF
A chatbot that answers from your own documents — and shows where each answer came from. No making things up.
LangGraph · Vercel AI SDK · pgvector
AI Insights / Summary
Automatic summaries and insights for your dashboards. Updated on a schedule, structured for easy display.
OpenAI · Anthropic · Promptfoo
Smart Onboarding
An AI assistant that guides new users through setup — adapting to what they actually need.
Vercel AI SDK · OpenAI
| Feature | Light €5,500 | Full €12,000 | Multi-Agent (Custom) |
|---|---|---|---|
| Number of features | 1 feature | 1 feature | Complex multi-agent |
| Answer appears live (word by word) | ✓ | ✓ | ✓ |
| Shows where answers come from | ✓ | ✓ | ✓ |
| High-quality search | optional | ✓ default | ✓ |
| Quality measurement system | ✗ | ✓ | ✓ workflow-level |
| Test set with real questions | ✗ | ✓ | ✓ |
| Automated quality checks | ✗ | ✓ | ✓ |
| Protection against failures | basic | full | full |
| Cost tracking | ✗ | ✓ | ✓ |
| Insight into how the AI behaves | ✗ | ✓ | ✓ |
| Bug-fix warranty | 14 days | 30 days | 30 days |
| Handover meeting | — | 90 min | 90 min |
| Timeline | 2 weeks | 3–4 weeks | 4–6 weeks |
| Price | €5,500 | €12,000 | €22,000–35,000 |
The Multi-Agent option is a custom build — start with an Audit or Strategy Sprint first so we know what to scope.
For your CTO — what we'll use
Default stack: Next.js, TypeScript, OpenAI or Anthropic for the AI brain, Postgres with pgvector for storing embeddings, optional Cohere or BGE rerankers for higher-quality search, Vercel for hosting. Quality measurement: RAGAS or Promptfoo, with LangSmith or OpenTelemetry for tracing. For Multi-Agent setups we pick the framework that fits your stack: Mastra or the Vercel AI SDK for TypeScript shops, Pydantic AI or LangGraph for Python, AWS Strands for AWS-native teams — with a durability layer (Temporal or Vercel Workflows) when a workflow runs for minutes or longer. Chosen per use case, never one-size-fits-all.
Most AI projects ship a demo that works on Tuesday and starts misbehaving on Friday. Models change, costs change, your data changes — and nobody notices until users complain.
We do it differently.
Before we write any code, we agree on a list of real questions your users would ask and the answers they should get. We test against that list while building. After launch, the same tests run automatically — every time the AI changes, every time the model updates.
If quality drops, you'll know on day one — not after your first angry customer email.
Plan it. Agree on what "good" looks like with a real test set.
Build the core feature.
Add quality checks, cost tracking, protection against failures.
Polish, hand it over, document everything.
- Per-customer quality testing if you have a multi-tenant product (separate add-on)
- Custom model fine-tuning
- On-prem deployment (separate Self-Hosted Add-On, +€3,500)
- Rebuilds of existing non-AI features (see MVP Sprint)
Need to host the AI on your own servers — for GDPR, compliance, or because your enterprise customers demand it? We add that on for €3,500. 1–2 weeks extra.