Auditable intelligence where capital is at stake.
In a fragmented, fast-moving market, allocation decisions need evidence that can be audited after the fact and trusted before it.
Use cases
Where allocation fails under pressure, and how the stack holds.
One fold per pain: what breaks, how Grand Thera's decision-grade AI stack resolves it, and an interactive figure to explore.
01 / 04
The pain
Allocation decisions run on stale exposure.
Positions span venues, custodians and asset classes. Consolidated exposure arrives after the market has already moved.
How Grand Thera solves it
TheraOS consolidates venues, custody and market data into one live exposure layer for every portfolio.
Portfolio exposure in real time, per client and per mandate.
Interactive figure · demonstration data
02 / 04
The pain
Client limits live in documents, not in systems.
Mandates, risk preferences and suitability rules are written down but enforced by people under time pressure.
How Grand Thera solves it
Client goals stated in natural language become machine-enforced risk rails; nothing outside the limits is recommended or executed.
Every allocation provably inside the client's limits.
Interactive figure · demonstration data
AIT Agents
The agents that address these problems.
Choose an agent to see what it watches and what it brings to a decision. If yours is not here, we build it.
03 / 04
The pain
Volatility regimes change faster than rebalancing cycles.
In digital assets and stressed markets, a regime shift can erase a quarter's return in days.
How Grand Thera solves it
AIT Agents detect regime shifts, simulate every proposed portfolio against scenarios and rebalance within tolerance.
Drawdowns contained to the client's tolerance, not the market's.
Interactive figure · demonstration data
04 / 04
The pain
Suitability and audit are reconstructed after the fact.
When a client or regulator asks why an order was placed, the answer is spread across systems.
How Grand Thera solves it
Proposal, simulation, limit check, approval and execution are written to a hash-chained decision ledger.
Any decision traced end to end, in seconds.
Interactive figure · demonstration data
Client case · RedMind
Financial intelligence in production.
RedMind uses TheraOS for its banking infrastructure and more than 20 auditable portfolios. AIT Agents monitor a fragmented, fast-moving market and support critical allocation decisions.
RedMind on TheraOS
Deployment at a glance.
- AIT Agents running in real time
- 60+
- Data sources consolidated
- 20+
- Critical workloads deployed
- 100+
Figures as published by Grand Thera.
RedMind stress test
The market breaks. The rails hold.
Every proposed portfolio is simulated against market scenarios before an order is executed, then rebalanced in real time.
Full case
Read how the stack was deployed at RedMind.
“What Grand Thera has built with Decision-Grade AI addresses a core executive challenge: acting with clarity under uncertainty.”
Decisions supported
From monitoring to allocation.
Portfolio monitoring
Continuous observation of auditable portfolios against defined risk and return thresholds.
Allocation support
Agents surface the evidence relevant to an allocation decision, with its uncertainty.
Regime awareness
Changes in market behavior distinguished from noise before they are acted on.
Auditability
Every recommendation traceable to its data, models and the decision it informed.
Open engineering
