Your data questioned.Your KPIs in plain English.Answer in under 3s.

Thursday, 5pm. You're prepping tomorrow's board. You need average basket per acquisition cohort across the last 90 days, crossed with origin channel. You ping the data analyst, on PTO. The data engineer replies: 'ticket logged, we'll look Monday'. You open Looker, the dashboard has been broken since the last Postgres migration. You end up exporting three CSVs, crossing them in Excel, walking into the board with a number you barely dare defend. Three follow-up questions later, the chair says: 'we'll wait for next time'. You know exactly what that means.

Forrester estimates that 67% of executives wait an average of 4 days for a simple data answer from their analytics team. McKinsey Global Survey 2025: companies that adopted a conversational BI layer make strategic decisions 2.8x faster and reduce their data backlog by 71%. Gartner predicts 60% of enterprise data queries will be in natural language by end of 2027. Hand-written SQL is becoming a structural bottleneck, not a sign of expertise.

Wikolabs installs AI systems built on open-source models, on your premises, paid once. No black box: your data, your prompts and your history stay in your infrastructure. We quote at a fixed price or on time and materials, never per ticket or per token, and we say before you sign what works and what does not yet.

Concretely: we connect your databases (MongoDB, PostgreSQL, Google Sheets) in 15 minutes, schemas analyzed, vectorized, semantic context ready. You open Chainlit, you ask 'average basket per acquisition cohort over 90 days, crossed with origin channel' in plain English. A large language model generates the multi-source SQL, runs it, returns a table in the conversation in under 3 seconds. You refine: 'segment by region'. The AI keeps context. No dashboard to maintain. No ticket. No waiting.