From signals
to strategy
The living foresight platform for regulated industries. It finds where your evidence disagrees, attacks every contradiction until only the real ones survive, and keeps four scenarios live for your board.
Europe’s grid & AILeading: Managed Constraint · 32%Read foresight 
Public sector 2030Leading: The Paperweight Renaissance · 49%Read foresight 
Banking 2030Leading: Platform Super-League · 33%Read foresight 
Czech automotive 2035Leading: The Boutique Engineering Lab · 45%Read foresight 
Europe’s rearmamentLeading: Wartime Industrial Discipline · 41%Read foresight Introducing the Monday brief
A living foresight platform that monitors the sources moving your industry, keeps four scenarios live as the world shifts, and delivers a decision-ready brief every Monday morning.
- What moved this week, traced to its source
- Which scenario it moved, and by how much
- What to do about it, ranked by stake and timing
- Built for strategy leaders in banking, energy and telco
A living foresight platform for your board
Describe a decision context. Six agents start researching it in seconds. Open the live Banking 2030 space
What future do you want to see?
Describe a decision context and the DSGHT.ai fleet maps the tensions, runs the scenarios, and surfaces the trade-offs.
Banking 2030 · Open Finance
Live19,979 sources · 1,442 claims · 850 tensions · updated 12 Sep 2026
By 2030, value in banking shifts from selling products on proprietary rails to orchestrating trusted data and programmable payments across contested platforms and settlement networks. Who controls distribution (Big Tech vs regulated incumbents) and how fast tokenized rails scale will determine margins, moats, and market power.
Banking 2030 · Open Finance
Live19,979 sources · 1,442 claims · 850 tensions · updated 12 Sep 2026
Open Finance and tokenization are projected to reach 1 billion users and $50B in savings by 2030.
Brittle and fragmented data infrastructure currently thwarts the industrialization of AI in banks.
The 'Front-End' of the future (Open Finance/Tokenization) is moving at a speed that the 'Back-End' (Legacy Data Core) cannot support. This creates a ceiling for innovation where apps exist but cannot scale or utilize AI effectively.
Strategic implication. Prioritize 'Infrastructure Modernization' over 'Product Innovation.' Without a unified data layer, the 2030 targets are mathematically unachievable.
Synthetic board review
Banking 2030 · Open Finance · 6 C-level personas
- CEONo 12-month, load-bearing execution plan — Decision Brief is truncated and lacks the three needle-moving moves, owners, budgets, and KPIs to bridge from today to the 2030 scenarios.
- CFOUnfunded mandates: the report asks boards to 'fund the data-core rebuild' and execute an enterprise post-quantum cryptography (PQC) migration without any capital plan, ROI, or stage gates, and the Decision Brief is incomplete ([R2] is truncated). These are Type 1, one-way-door investments that cannot be reversed cheaply.
- CTODecision Brief is incomplete and the core 'data-core rebuild' lacks a concrete target architecture, phased plan, and success SLOs; 'R2 Build a unified conse...' is truncated and leaves no executable blueprint.
- COOThe Decision Brief is incomplete on the load-bearing data/consent program — [R2] is truncated and leaves the unified consent/data layer (the pacing item for Tension-003) without owners, phasing, capacity plan, or KPIs.
Monday brief
Banking 2030 · Open Finance · update of 12 Sep 2026
What moved
Major platforms licensed as financial information providers/users in large markets (e.g., India Account Aggregator, Brazil Open Finance)
Brazil – Datanomik authorised by Banco Central do Brasil as a Payment Transaction Initiator and participant in Brazil's Open Finance, connecting to 30+ Brazilian financial institutions (Aug 2026). India – Account Aggregator (AA) ecosystem showing scale: 17 licensed Account Aggregators (13 with live integrations) and RBI recognition of Sahamati as the AA SRO; the AA network reports 1,120 live regulated financial entities on the rails (June 2026). These developments indicate major platform and platform-adjacent participants gaining licensed footholds in large markets.
Reserve Bank of India (RBI) / National Payments Corporation of India (NPCI)Scenario shift
- Sovereign Rail, Narrow Gate32% 30%2%
- Thick Walls, Thin Pipes14% 13%1%
- Open Hands, Old Tracks26% 24%2%
Recommended action
Spin out a regulated Balance-Sheet-as-a-Service unit with ring-fenced risk governance and platform SLAs
- Decide
- Assess by 2028 or when BIS/CPMI reports tokenized settlement >15%
- If delayed
- Platforms will lock in rival banks as default risk/treasury providers, making later entry a price-taker position with little bargaining power.
Source trace
- 30%India is forecast to hold 47% of the global Open Finance user base (479 million users) by 2030.deloitte.com · claim-042
- 20%Brazil processes 3 billion API calls per week with 70 million connected accounts.cnb.cz · claim-018
- 15%Brazil achieved open banking implementation in 6 months by using established standards from the Open ID Foundation.ripae.com · claim-046
Six agents read everything
so you see what holds
Official statistics, regulators, markets and research, read continuously across 17 live future spaces.
562 indicators
IMF392 series
ECB68 series- eurostat343 series
European Parliament58 documents
500 records
CISA860 advisories
341 markets
363 papers
410 preprints
450 papers
Semantic Scholar218 papers- +53more connectors the agents can call, from central banks and regulators to patent offices, energy grids and conflict data.
- FRED
- BIS
- OECD
- DBnomics
- Our World in Data
- WHO Global Health Observatory
- CNB ARAD
- CNB press
- NBP
- EBA
- ESMA
- EIOPA
- FMA Austria
- SEC EDGAR
- ESEF / XBRL filings
- Earnings calls
- Finnhub
- CoinGecko
- Manifold
- EUR-Lex
- TED procurement
- CORDIS
- CEN-CENELEC
- OpenSanctions
- Hlídač státu
- ARES
- ENTSO-E
- EIA
- Ember
- OTE
- Climate TRACE
- Open-Meteo
- NASA FIRMS
- ACLED
- UCDP
- GDELT
- Cloudflare Radar
- EPO
- USPTO
- ÚPV
- CORE
- Dealroom
- Adzuna
- MPSV
- GUS
- KSH
- DATAcube SK
- CEE think tanks
- Hacker News
- Wikipedia pageviews
- Bluesky
- Mastodon
- X watchlist
Counts are the items each feed delivered, summed over the live spaces. On top, the six agents read the open web.
- World BankAustria: GDP (current US$) — 2025Data feed
- SAGE JournalsAcademic article on regulation and AI risksMarket Intel
- ECBEUR/HUF daily reference rateData feed
- World Bank BlogsGreen growth, green jobs, and labor marketsTrend Scout
- IMFCZE: Unemployment rate (% labor force)Data feed
- Read238,123sources
- Turned into claims15,286each traced to its source
- Contradictions found9,691where claims disagree, kept apart for you to judge
Foresight for regulated industries
Live future spaces our agents keep current, week after week.
This is strategic foresight
Two founders, two specialties
20 years of strategic foresight in regulated industries, plus a track record of designing and shipping AI-native products across CEE.
Michal Strnadel
Chairman of the Czech UX Association. Ex-strategic designer at Česká spořitelna, design lead at Slevomat, head of digital services at the Ministry of Interior.
LinkedIn
Jiří Devát
Ex-Country Manager Microsoft CZ/SK, ex-GM Cisco CZ, ex-Vice Chair Czech Airlines. 20 years of strategic foresight across regulated industries.
LinkedInHow we think about the next decade
Essays by the founders on foresight, strategy and AI.
The World User's Guide: 2026 Edition
Three civilizational ruptures — personal computer, internet, and AI — each removed a barrier between the human being and the World. But when the final barrier falls, a stranger question opens: who, in fact, is using whom?
Between Hype and Reality: Four AI Futures Based on What We Actually Know
AI per unit is cheaper than ever, but total costs are rising as autonomous agents consume most tokens. Adoption is lagging capabilities — here's a data-driven look at where AI is heading and four plausible futures.
Time to Innovation: Why Your Competitors Innovate Faster
A late product generates 33% lower profit over five years. Time to Innovation measures the organizational capability to turn opportunity into outcome — and data shows fast innovators are 18x more likely to be disruptive in their industry.
The Obsolescence Trap: Why Long-Term Plans Kill Innovation
A Czech bank is approving an AI project right now. It will be finished in 2027. The problem: nobody in that room knows what AI will look like in two years. This is the Obsolescence Trap — and it's closing faster than ever.
Questions, answered
How is DSGHT.ai different from traditional foresight consulting?
A classic foresight project gets you a €50,000 PDF report after three months, and it is out of date a month later. DSGHT.ai is a permanent layer underneath your strategy — a platform that keeps scenarios live 24/7 and tells you every Monday what shifted. It does not replace strategic thinking; it is the infrastructure underneath it.
What does “Living Foresight” actually mean?
Traditional foresight is a snapshot — four scenarios fixed in a single moment, static probabilities, recommendations that do not move. Living Foresight means the scenarios update themselves: probabilities shift as new signals arrive, recommendations rewrite, and you can see in real time which way the world is leaning. Instead of a PDF, a dashboard that reacts.
What are Future Spaces?
A Future Space is a thematic workspace — for example “Banking 2030: Open Finance” or “CEE Energy Transition.” You define the industry, region, and horizon, and six agents start monitoring sources, generating four scenarios, and tracking signals. You can run several Future Spaces in parallel: one for the core business, another for new markets, a third for the regulatory environment.
How quickly can I get started?
Setting up your first Future Space takes about 10 minutes. The six agents start monitoring within seconds. You will see the first complete set of scenarios within 24 hours. The first Monday brief lands a week after onboarding.
How do you ensure intelligence is explainable and auditable?
Every claim in the dashboard links to its primary source — click through and see where the answer came from. Every change in scenario probability has a reasoning trace: which signals moved it, how strongly, and why. No black box.
Is it safe to use with internal strategy data?
Your inputs (decision context, internal documents) stay in an isolated workspace. The agents only read sources you point them at — public data, your own documents, or sources you have licensed. No client data leaves the EU, and no model is trained on your inputs.
Does DSGHT.ai support MCP (Model Context Protocol)?
Yes. DSGHT.ai runs a public MCP (Model Context Protocol) server so AI agents like Claude, Cursor, and ChatGPT can connect to it directly — free, read-only, no account or API key. Your agent can resolve macro claims against the right country’s authoritative data and read our published foresight (tensions, scenario matrices, reports), all with cited provenance. The endpoint is https://www.dsght.ai/mcp, with a discovery manifest at /.well-known/mcp.json. See the connect guide at /install.
Still have questions? support@dsght.ai
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