Financial Services
PatternDocument handling under confidentiality
Borrower financials and credit files processed inside the boundary, with only minimised, non-identifying context escalated when a harder judgement is needed.
Use the smallest model that can be trusted.
Sending every request to the largest available model is expensive, hard to govern, and often unnecessary. We design routing architectures where private open-weight models, specialized models, deterministic rules, frontier models and human review each handle the work they are actually suited to — under your control.
The business problem
One model for everything is a governance problem and a cost problem.
A single frontier endpoint for all workloads means sensitive data leaves your boundary for tasks that never needed to, spend scales with volume rather than with difficulty, and you inherit a vendor's roadmap as your architecture. In regulated or high-risk environments that is frequently the reason a system cannot be approved at all.
What that looks like
- Sensitive records leaving the environment for routine classification
- Frontier pricing applied to work a small model or a rule would settle
- No way to demonstrate which model made which decision, or why
- Architecture coupled to one provider's availability and terms
What Catalyze builds
What we build
An escalation path, not a single endpoint. Each tier is chosen deliberately, and the choice is recorded.
- 01
Private open-weight deployment
Open-weight models running inside your environment or VPC, so data used for routine work never leaves your boundary.
- 02
Specialized models
Smaller task-specific models — classification, extraction, ranking — which are cheaper, faster and easier to evaluate than a general one.
- 03
Deterministic logic
Rules, calculations and lookups for anything with a defined right answer. A threshold test does not need inference.
- 04
Selective frontier escalation
Frontier models reserved for genuinely hard reasoning, with the data minimised before it is sent and the decision logged.
- 05
Human review for exceptions
High-risk and low-confidence cases route to a person, with the full routing history attached.
- 06
Routing policy and observability
Which tier handled which request, at what confidence and what cost, visible per workflow rather than as one aggregate bill.
Architecture
Intelligent routing
A request descends only as far as it needs to. Most stop early — which is the point, and where the privacy, cost and governance properties come from.
01Document / Request
Work enters with its classification, sensitivity and required confidence already known.
02Private Model
Open-weight model inside your boundary. Handles routine understanding without data egress.
03Specialized Model
Task-specific extraction, classification or ranking where a general model is overkill.
04Rules / Calculations
Deterministic logic for anything with a defined answer. Fast, free, and exactly auditable.
05Frontier Model
Only when the task genuinely requires it, with inputs minimised and the escalation recorded.
06Human Review
High-risk exceptions and low-confidence outcomes, with the full routing trail attached.
Each tier has an exit. A request descends only when the tier above cannot resolve it at the required confidence — which is where the privacy, cost and governance properties come from.
Example use cases
Where this applies
Patterns we design for. These are architectural applications, not claimed deployments.
Healthcare
PatternClinical and operational records
Environments where residency and access rules make routing to an external endpoint a compliance decision rather than a technical one.
Enterprise
PatternHigh-volume classification
Workloads where the per-request cost difference between tiers compounds into the dominant line item.
Regulated Operations
PatternDecisions that must be explained
Processes where a reviewer has to see which component produced a result and on what basis, not just what the result was.
Technology & integration
Deployment and control surface
Described at category level. The right combination depends on your residency, security and procurement constraints — we design to those rather than to a preferred stack.
Named platforms
- AWS
Deployment
- In-VPC inference
- On-premise
- Dedicated tenancy
- Hybrid routing
Model tiers
- Open-weight
- Task-specific
- Deterministic rules
- Frontier (selective)
Governance
- Data residency
- Egress policy
- Per-tier decision logs
- Cost attribution by workflow
Related insights
Our thinking on this.
Questions
What buyers ask us about Private AI.
Does private AI mean no frontier models at all?
No. It means frontier models are one tier among several rather than the default, used where the reasoning genuinely requires them and with inputs minimised first. Refusing them outright would cost you capability; routing everything to them costs you control.
Where does the data actually go?
That is a design decision made per workflow and per tier, and it is explicit. Routine work can be handled entirely inside your environment. Where escalation is warranted, what is sent is minimised and the escalation is logged.
Is this mainly a cost exercise?
Cost is usually the most visible benefit, because the tier difference on high-volume work compounds. But in regulated environments the governance properties matter more: being able to show which component decided what is often the condition for approval.
What happens when better models arrive?
Tiers are swappable behind the routing policy. That is the reason for building it this way — the architecture should absorb a model change rather than be defined by it.
Can you work within our existing security and procurement constraints?
That is the starting point rather than a limitation to work around. Residency, egress and tenancy requirements shape the routing design from the first conversation.
Tell us about the workflow. We'll tell you whether Private AI is the right place to start.