Triuna LabsDiscuss your projectCurrent-state system map
Components, data flows, external dependencies, access boundaries and responsible owners.
Consulting · Triuna Labs
AI systems you can understand, trust, and operate.
Triuna Labs assesses and builds AI products and workflows as whole systems: people, data, software, decisions, controls, and operations. Start with the system you have, the decision you need to make, and the evidence needed to move forward. The work stays visible through linked findings and clear handoffs.
When to bring us in
Recognize one of these situations?
01 / PRODUCTION
Your AI prototype is stuck before production.
Identify the integration, ownership, evaluation and operating gaps blocking the next step.
Assess the path forward ↘ 02 / DOCUMENTS & RAGYour answers are difficult to check.
Examine retrieval, source traceability and failure cases against the questions your team actually asks.
Inspect the evidence path ↘ 03 / AGENT WORKFLOWSYour agents need clearer operating controls.
Review tool permissions, approval points, evaluation and recovery paths before expanding their authority.
Review the boundaries ↘A focused first engagement
AI System Readiness & Architecture Assessment
Understand the system you have, the risks blocking progress, and the next investment worth making. Map the whole production AI system: people, workflows, data, software, model and tool authority, outside dependencies, and operating limits. The assessment can stand alone.
Evidence-linked findings
What was observed, what remains unknown, and the risks or gaps that affect the next decision.
Prioritized action plan
Recommended changes, dependencies, validation steps and acceptance criteria for the agreed scope.
Decision walkthrough
A review with the responsible team to examine findings, tradeoffs, ownership and the next step.
Bounded scope. Explicit handoff.
We agree the systems, access, representative workflows, deliverables and review points before work begins. Fees and timing depend on those boundaries and the evidence available. Any implementation is scoped separately after the findings are reviewed.
Fictional reporting sampleInspect a sample deliverable ↗Versioned progress, linked evidence and open decisions.
Experience & backgroundMeet your principal architect ↗Paul Woll · 30+ years across enterprise systems and applied AI.
Our own working productInspect AINewsIQ’s methods ↗Source provenance, external integrations and operating controls.
Discuss an assessment or project
What is blocking your next step?
Tell us about the system, the problem and the decision you need to make. We will use that first conversation to identify a suitable starting point: an assessment, architecture review, focused implementation or ongoing advice.
Assess / Find the risks and unknownsEquip / Leave your team with a usable recordBuild / Implement agreed changesAdvise / Improve what is in operation
Prefer a direct note? Email Paul →
You work directly with Paul Woll, founder and principal architect. His 30+ years span defense systems, enterprise platforms, SaaS and applied AI.
Inspect the work
Explore a versioned, fictional report with linked evidence, open decisions and work in progress.
Open the sample report ↗See how an internal team built a useful system record while client code stayed inside its approved workspace.
Read the anonymized account ↓Explore a public AI news product with source provenance, external integrations and documented checks. Product work, distinct from client engagements.
Inspect AINewsIQ’s methods ↗Review tools for release evidence, data quality and agent coordination as examples of the engineering practice.
Browse the tools ↗1
Describe the system or decision
Describe the system or decision
2
Agree the scope and evidence
Agree the scope and evidence
3
Review the work as it progresses
Review the work as it progresses
Explore nine example AI consulting challenges and the proposed work →
Where we can help
Engineering for consequential decisions.
Each engagement starts with the decision, constraints and evidence available. Architecture reviews, technical advisory, proofs of concept and full product development can be scoped independently or connected as the work evolves.
AI Strategy & Architecture
Problem: Teams need a credible path from an AI idea to a system they can operate.
Approach: Map workflows, data boundaries, decisions and technical options before committing to a design.
Possible outcome: An architecture and prioritized implementation plan grounded in the existing environment.
Custom AI Products & Applications
Problem: Generic tools cannot cover a specialized workflow or product experience.
Approach: Design the interface, service boundaries, model use and operational controls together.
Possible outcome: A working application or bounded vertical slice with source and handoff.
Agentic AI & Workflow Orchestration
Problem: Multi-step work crosses tools and people, but responsibility is hard to trace.
Approach: Define authority, tool access, checkpoints, failure paths and human review.
Possible outcome: A workflow with explicit operating limits and an inspectable run record.
Document Intelligence & RAG
Problem: Answers are buried in mixed files, and retrieval can lose source context.
Approach: Evaluate document structure, extraction, retrieval and evidence links against representative questions.
Possible outcome: A tested document pipeline or prototype with source traceability.
AI Evaluation, Security & Governance
Problem: Promising output is difficult to approve without clear quality and risk evidence.
Approach: Define evaluation cases, access boundaries, review points and change records.
Possible outcome: A decision brief, risk register and repeatable evaluation process.
Technical Prototyping & Modernization
Problem: Existing systems constrain new product or AI work.
Approach: Build a small demonstrable slice, measure integration friction and plan the next migration step.
Possible outcome: A validated prototype or modernization path with known tradeoffs.
See the engineering in action
Trace an answer back to its source.
This local demonstration pairs illustrative structured results with the exact passages that support them. Select a result to inspect its source. The sample is synthetic, and no file or data is sent to a service.
DOCUMENT INTELLIGENCE / ILLUSTRATIVE SAMPLELOCAL BROWSER DEMO
01 / SOURCE DOCUMENTOperations review memo
SYNTHETIC OPERATIONS MEMOILLUSTRATIVE SAMPLE
Operations review memo
Illustrative document · Reference SAMPLE-042
Service: Document intake and review
System owner: Platform Operations
Next review: 15 November 2026
Current risk: Manual exception handoffs have no recorded owner.
Required follow-up: Assign an exception owner and verify the escalation path.
Prepared for a demonstration. No client material.
02 / STRUCTURED RESULTSReview each field
Illustrative, precomputed values. Select a field to highlight its source in the document.
Showing source for System owner: Platform Operations.
This demonstrates review and provenance, not live extraction or a production accuracy claim.
Engagement model
A clear path from question to operation.
Discover → Architect → Prototype → Build → Validate → Deploy describes a full delivery path. An architecture review, advisory engagement or proof of concept may end earlier, with its own agreed outputs and acceptance criteria.
- 01Discover
Define goals, people, systems and constraints.
- 02Architect
Choose boundaries, components and review points.
- 03Prototype
Test the uncertain parts with a bounded slice.
- 04Build
Implement the agreed workflow or product.
- 05Validate
Check behavior, failure cases and evidence.
- 06Deploy
Hand off, operate and plan improvement.
Ways to work together
Start where support matters most.
Choose a starting point: assess a system, equip your team, build a focused solution, or get ongoing technical advice. Each can stand alone or connect with other work as the need becomes clear.
Before work begins We agree on the intended outcome, access boundaries, deliverables, reporting cadence, evidence expected and acceptance criteria.
Read the four starting points and possible outputs
System and workflow assessment
Best when: you need a reliable current-state picture before funding a change. Map goals, people, processes, dependencies, data, access, release paths, operating risks and unknowns.
Possible output: evidence-linked decision brief, system map and prioritized gap register.Equip the team to operate
Best when: the system works, but knowledge is concentrated or documentation is stale. Align architecture notes, process maps and runbooks with actual operations, then walk owners through the record.
Possible output: reviewed runbooks, practical training and owned handoffs.Focused implementation
Best when: the decision and operating boundaries are understood. Deliver a bounded integration, agent workflow, internal tool or decision surface with validation and review points.
Possible output: a working vertical slice with source, checks and handoff.Ongoing technical advisory
Best when: your team owns the system and needs periodic senior review. Examine failure patterns, operating burden and roadmap choices, then target further work where evidence supports it.
Possible output: decision briefs, prioritized changes and reviewed improvements.What the proposal makes explicit
The decision to support, systems and access in scope, named outputs, reporting cadence, client responsibilities, acceptance criteria and handoff.
What shapes the effort
System count, data sensitivity, integration points, available evidence, review needs and deployment boundaries. Fees and schedule belong in the proposed scope.
During the engagement
Visible progress. Reviewable proof.
During the engagement, you receive work in progress reports and evidence packets. Each update shows completed and current work, blockers, decisions and supporting artifacts. The proposal sets the cadence and the evidence expected for each deliverable.
A record you can use while work is happening
- 01 / PROGRESSWork in progress reports
Completed work, current tasks, blockers, owners and the next checkpoint.
- 02 / EVIDENCEEvidence packets
Relevant source changes, test results, observations and artifacts linked to the claims they support.
- 03 / DECISIONSDecision and handoff trail
Options considered, approvals needed, accepted outputs and remaining work.
Delivered in your approved workspace. Reports can live in a client-owned project space, intranet or document library when permitted. A separately hosted view is an option only when your access and security review allows it. The proposal sets access, retention, update cadence and final handoff; a Triuna-hosted SaaS account is not required.
See a fictional report excerptENGAGEMENT / REPORTING IN PROGRESS
01 / WORK IN PROGRESSProgress report
COMPLETEDChanges and outputs
IN REVIEWQuestions and decisions
NEXTOwner and checkpoint
02 / SUPPORTING RECORDEvidence packet
↗ Source or artifact
↗ Test and observation
↗ Decision and acceptance
Fictional sample / progress update
A working record, while decisions are still open.
COMPLETEDCurrent-state map reviewed
The team mapped the system boundary and named owners for the main dependencies.
EVIDENCEFindings tied to source
An inventory excerpt and review notes support the map and record one unresolved exception.
DECISION NEEDEDConfirm the next access step
The client owner decides who may inspect exception logs before the next checkpoint.
Ferrowick Mutual, its engagement and every record are fictional. Version 1 is a historical sample snapshot dated 2 October 2026.
Anonymized engagement
From opaque work to a usable record.
A company had little visibility into a system built through outside work. Its access process also prevented Triuna Labs from viewing the code directly, although the company's engineers could access it. The engagement gave those engineers a structured way to investigate the system and maintain an evidence-linked record.
What the engagement delivered
Working within the company's access process, Triuna Labs trained engineers with authorized repository access and developed role-specific prompt packs and skills for the person responsible for the assessment. The internal team used them to examine code and related materials, interact with the resulting corpus and document what the system actually did. Findings informed further tuning of the investigation tools.
A larger prompt set generated an internal HTML reporting site with executive summaries, technical documentation and findings linked to their supporting evidence. The review also surfaced external processes, missing knowledge and assigned follow-ups needed for fuller runbooks, security and risk assessments, business continuity planning and possible AI expansion.
JIK / Just Enough Knowledge
The access boundary supported trust: code remained with the company's authorized team, and Triuna Labs gained only limited knowledge of its IP. Leaders could review findings alongside their sources, while engineers had a repeatable way to extend the record and request targeted help.
ENGAGEMENT / KNOWLEDGE TRANSFER01 → 04
01 / INPUTCode and documents in the client workspaceKept under client control and investigated by approved staff.
02 / TEAM CAPABILITYRole-specific investigationTraining, prompt packs and task-specific skills.
03 / WORKING RECORDInternal reporting site
Executive summariesLinked evidenceTechnical documentation
04 / NEXT DECISIONSGaps, owners and follow-upsInputs for runbooks, risk review and continuity planning.
Published tools
A glimpse of the practice.
A selection of published tools offers a look at the engineering craft behind Triuna Labs. They cover specific tasks in release evidence, data quality and agent coordination. Client work is designed for the system and decision at hand, with its own architecture, implementation and evidence trail.
Release Brief
Turns a Git revision range and supplied evidence into an infographic brief covering collaboration, tests, security, supply chain, and operational readiness.
Explore Release Brief ↗CSV Profile
Finds structural problems, nulls, type conflicts, duplicates, category variants, and outliers, with optional aggregate-only semantic review.
Explore CSV Profile ↗Message Routing
Routes a change or question to relevant active sessions and reports whether each message was delivered, held, unavailable, or failed.
Explore Message Routing ↗Before we work together
The practical questions.
Bring the system or decision, the people who own it, and any known constraints. A short first note is enough; restricted data and credentials can wait for an approved access path.
When is Triuna Labs a good fit?
When a team needs senior hands-on help across the system: from a hard decision or incomplete record through implementation, validation and operation. A bounded assessment is a useful starting point when the right build is still unclear.
Can an assessment stand alone?
Yes. A scoped assessment can end with an evidence-linked system map, decision brief, prioritized gaps and owners. A build is a separate decision.
Who does the work?
You work directly with Paul Woll, founder and principal architect. Any additional roles or third parties would be identified in the proposed scope and reviewed before access.
Where do the code, reports and evidence live?
The work can use a client-approved repository, project space, intranet or document library. Access, permitted tools, retention and final handoff are agreed for each engagement. The vendor-review page lists the questions to confirm.
Who owns the deliverables and IP?
Ownership, permitted reuse, confidentiality and handoff are specified in the negotiated agreement and statement of work. The access model can keep client code with authorized client staff while still producing a reviewable record.
How are schedule and fees determined?
The proposal sets them against the system boundary, access, available evidence, integrations, review needs and named outputs. Assessment, team enablement, implementation and advisory can be scoped separately.
What does progress look like while work is underway?
Updates identify completed and current work, blockers, decisions, owners and supporting artifacts. The proposed scope sets cadence and acceptance criteria. See the fictional report format.