Data, AI and fintech engineering — end to end.
Four practices that share the same people, the same tooling and the same standard: production-grade systems, built fast with an agent-first approach.
Data platforms & real-time systems
We design and build the data backbone of a product or an organization: ingestion, modeling, storage and serving, from the first pipeline to systems processing very large event volumes in real time.
- 1.1Data architecture & modeling
- 1.2Streaming and batch pipelines
- 1.3Low-latency, real-time services
- 1.4Cloud infrastructure & cost control
Analytics & dashboards
Full-stack analytics applications on top of your data: KPI design, metric layers, interactive dashboards, admin consoles and the APIs behind them — built as products, not as reports.
- 2.1Analytics & BI applications
- 2.2Admin and operations dashboards
- 2.3REST / WebSocket APIs
- 2.4Ad-tech and measurement data
AI-native software, agents & applied R&D
Software designed to be operated by AI agents under human direction, plus hands-on applied research: language models, speech recognition, fine-tuning and model serving.
- 3.1AI-native frameworks & agentic workflows
- 3.2Process automation with AI agents
- 3.3LLM integration, fine-tuning & serving
- 3.4Speech / voice recognition R&D
Finance & trading technology
Technology for systematic investors: market-data engineering, backtesting and research platforms, risk and execution systems. This is where our own gtrade platform and the two free news indexes, OIL-F6 and EQ-S10, come from.
- 4.1Market-data ingestion & normalization
- 4.2Backtesting and research platforms
- 4.3Risk, margin & execution systems
- 4.4News and alternative-data signals
How we work together
Thinking Text is deliberately small: a senior core, with specialists brought in per project.
Fractional CTO & advisory
Technical strategy, architecture reviews and data / AI roadmaps for leadership teams, startups and investors.
Hands-on build
A senior-led team, assembled for the project, delivering a platform or product end to end — and handing it over cleanly.
Applied R&D
Time-boxed research and prototypes for hard problems: real-time ML, language and speech models, quantitative signals.