REAL-TIME + AI

Real-time processing turns AI into an operational control layer

Without batch windows, every balance, transaction, and state change is current. That improves day-to-day finance control and makes AI agents materially more useful for fraud, risk, and decisioning.

JUST-IN-TIME ARCHITECTURE

No batch jobs. The core posts as events happen.

Solid is built without batch dependencies. There are no overnight jobs that need to land before downstream systems can read accurate state — every transaction, balance change, and product event is processed as it happens. Removing that batch layer is what makes everything else on this page possible.

Continuous calculation

  • Balances, available credit, and exposures recompute as each event lands
  • Interest accrual, fees, and provisions advance continuously rather than on a nightly cycle
  • Posting, invoicing, and bookkeeping flow from the same stream of events the rest of the system reads
  • The same numbers are visible to servicing, risk, and finance at the same moment

Why JIT, not batch

  • No end-of-day window to reconcile or recover from
  • No special "current value" estimators bolted onto a batch ledger
  • Decisioning, fraud, and AI agents read live state instead of stale snapshots
  • Operating cost is lower because there's no second batch pipeline to run

WHAT CHANGES

Current state replaces end-of-day snapshots

Real-time isn't a feature bolted onto a batch system — it's an architectural property. When the core itself posts continuously, every downstream consumer sees current state without rebuilding it from exports.

  1. LIVE EVENT

    Transaction enters Solid

    The event is ingested the moment it happens — no batch window, no staging table.

    T + 0 ms

  2. STATE JOIN

    Context from live state

    Customer, account, limits, and signals are read from current state — not rebuilt from overnight exports.

    T + 2 ms

  3. MODEL

    Score risk and intent

    The selected AI model runs on a real-time context window and returns a decision in milliseconds.

    T + 50 ms

  4. DECISION

    Approve, hold, or escalate

    The outcome is applied before settlement finalizes — not after the loss has left the building.

    T + 60 ms

BY USE CASE

Benefits of real-time across the bank

The same underlying property — continuous, ordered state — shows up differently across fraud, finance, operations, and AI agent workloads. Each benefits from direct access to live context.

Benefits of realtime by use case

Detect and act while risk is still in-flight.

  • Score suspicious behavior with current balances, events, and linked context.
  • Hold, route, or escalate before settlement completes.
  • Preserve complete event lineage for investigation and regulatory follow-up.

Keep finance decisions based on current numbers.

  • Continuous access to current reporting without end-of-day lag.
  • Less reconciliation effort between finance, operations, and risk teams.
  • Live exposure views improve daily liquidity and planning decisions.

Run operations as a steady flow, not nightly catch-up.

  • Remove batch windows and reduce time-bound incident risk.
  • Smooth infrastructure load instead of expensive nighttime peaks.
  • Resolve exceptions continuously, not from stale next-day backlogs.

Make frontier AI models more accurate and efficient.

  • Ordered live deltas improve context quality for model reasoning.
  • Incremental prompts reduce token waste and inference overhead.
  • Fast simulation loops support policy testing and model tuning.

CAPABILITIES

What real-time unlocks for AI workloads

Three properties matter to AI systems built on top of a core: earlier action, better context, and lower compute waste. All three come from the same architectural choice.

Earlier fraud interruption

Action happens while the transaction chain is active, reducing loss propagation.

Stronger context quality

AI consumes ordered deltas from current state, improving signal over fragmented snapshots.

Lower token and compute waste

Incremental prompts and no batch windows cut both inference overhead and infrastructure peaks.

TALK TO THE TEAM

Bring your fraud, finance, or agent workload to the team

Schedule a call to walk through how live core state shows up in your workloads.

Schedule a call See architecture page