FINANCE · FINTECH · LEGAL
· SMALL BUSINESS
AI that works the way your firm is examined.
ALODEEL designs and implements agentic workflows for small and large institutions, connecting your people, processes and systems on a harness built for trust, reproducibility and fully auditable trajectories.
- Reproducible
- pinned models, versioned prompts
- Auditable
- every run logged and replayable
- Supervised
- human approval where it counts
Track record across
- OWL AI
- Incubator School
- Liberty Mutual Investments
- CPPIB
- FrontPoint / Copia Capital
- Mesirow Advanced Strategies
The problem
Most AI in financial services never survives risk review.
Not because the models are weak — because the workflows around them cannot be explained, repeated, or evidenced.
Pilots that never reach production
Impressive demos stall at the risk review because nobody can show how the model reached its answer.
Analyst time spent on retrieval, not judgment
Skilled staff rekey data between the CRM, the data room, the spreadsheet, and the memo.
Knowledge trapped in documents
Credit files, IC memos, term sheets, and policy PDFs hold the answers but cannot be queried.
No audit trail for AI decisions
Regulators, LPs, and internal audit ask what happened on a given run, and there is no record.
Non-reproducible outputs
The same input produces a different answer on Tuesday, so the workflow can never be relied upon.
Unclear where value actually is
Teams are told to 'use AI' without a ranked, quantified view of which processes are worth automating.
What ALODEEL does
From observed work to a workflow your auditors can follow.
- 01
Identify opportunities
Rank candidate processes by value, feasibility, and risk exposure.
- 02
Map the current workflow
Document every handoff, control point, system, and exception path as it exists today.
- 03
Design the target workflow
Split responsibilities between agents and humans, with explicit approval gates.
- 04
Build and connect
Implement the harness, integrations, evaluations, and monitoring.
- 05
Train the team
Enable operators and reviewers to run, question, and correct the system.
- 06
Measure and optimize
Track accuracy, escalation rate, cycle time, and cost against a baseline.
Services
A staged engagement, not an open-ended retainer.
Each stage produces something usable on its own, and you decide whether to continue.
AI Workflow Audit
A structured examination of your current processes, tools, bottlenecks, and repetitive work — ending in a ranked opportunity list rather than a slide deck.
- Current-state workflow map
- Ranked AI opportunities with value estimates
- Feasibility, model, and regulatory risk assessment
- Estimated time and cost savings per workflow
Workflow Blueprint
The future system is designed, argued, and agreed before a line of production code is written.
- Future-state workflow with trajectory definition
- AI and human responsibility split
- Integration and data-access plan
- Data requirements, retention, and residency
Build and Implementation
We create, evaluate, and deploy the workflow on a harness built for reproducibility and review.
- Working agentic workflow in your environment
- Integrations to core, CRM, data room, and document stores
- Regression and evaluation suite with pass thresholds
- Full trajectory logging and replay
Optimization and Support
Workflows drift as models, vendors, and policies change. We monitor and keep them honest.
- Continuous workflow monitoring
- Error, exception, and escalation review
- Prompt, retrieval, and model improvements
- New integrations as scope grows
Example use cases
Where firms like yours start.
Bounded, high-volume, easy to verify — the workflows that earn trust before they earn headlines.
- 01Deal sourcing, screening, and qualification
- 02Investment memo and report generation
- 03Email triage, routing, and drafting
- 04Client and member service assistance
- 05Document extraction and classification
- 06Internal knowledge assistants over policy and precedent
- 07Meeting summaries and follow-up task creation
- 08CRM and pipeline data synchronization
- 09Research and decision-support systems
- 10Reconciliation and exception handling
How it works
Five stages, each with a defined exit.
Discover
1–2 weeks
Interviews, observation, and system access review. We watch the work happen rather than relying on process documentation.
Design
2–3 weeks
The target trajectory is specified: which steps are deterministic, which are model-driven, and where a human must sign.
Build
4–10 weeks
Implementation on a harness with versioned prompts, tool contracts, structured outputs, retries, and full trajectory capture.
Launch
2–4 weeks
Shadow-mode running against real volume, then a staged cutover with hypercare and a documented rollback path.
Improve
Ongoing
Monitoring, exception review, and periodic re-evaluation as models and policies change underneath you.
Why ALODEEL
Practical outcomes rather than AI theater.
Built around your actual operations
We start from observed work, not a reference architecture. The workflow matches how your team really operates.
Reproducibility as a requirement
Versioned prompts, pinned models, structured outputs, and a regression suite that must pass before anything ships.
Auditable trajectories
Every run records inputs, tool calls, retrieved sources, model versions, and approvals — and can be replayed.
Human oversight where judgment matters
Approval gates are designed in, not bolted on. Credit, compliance, and client-facing outputs never auto-send by default.
Vendor-neutral recommendations
No reseller margin, no platform lock-in. We select the model and tooling that fits your risk posture and budget.
You own everything
Your data, your prompts, your code, your evaluation sets. Documentation and training are part of the engagement, not an upsell.
Proof
Outcomes, not logos.
ALODEEL is a specialist practice led by Nicholas B. Fok, with two decades across institutional asset management, applied AI, and company building — from $80B general-account portfolios to AI-native platforms shipping today.
OWL AI · 120+ institutional firms
Multi-stage reconciliation across filings & transcripts
Prompt guardrails making RAG production-ready
>95% on-time delivery across institutional clients
Source-constrained agentic RAG with page-level citation
Risk budgeting & SAA on $80B general account
$240M portfolio at CPPIB
Capital discipline applied to inventory at Duli Capital
Security and responsible AI
Controls designed for examination, not for a marketing page.
Data handling
Minimum necessary data, defined retention, and no training on your content by default.
Human approval
Consequential actions require a named reviewer before execution.
Access control
Least-privilege service accounts, scoped tool permissions, and full access logging.
Confidentiality
NDAs as standard, segregated environments, and named-personnel restrictions on request.
Vendor selection
Model and vendor choices assessed against your third-party risk requirements.
Testing and monitoring
Pre-release evaluation gates plus production monitoring for drift and escalation rates.
FAQ
The questions that come up first.
Next step
Find your best AI workflow opportunity
A 30-minute discovery call: we look at two or three of your current processes and tell you plainly which are worth automating and which are not.