Lens Engine

One wiki. Multiple lenses. Better decisions.

The same source-backed wiki can answer different questions depending on the lens applied: alignment, optimization, competitive threat, AI visibility, governance, leadership review, or operational execution.

Core lens library

Eight lenses. One context layer.

Lens

Alignment Lens

“Are teams operating from the same priorities?”

Lens

Optimization Lens

“Where are workflows duplicative, slow, or over-resourced?”

Lens

Leadership Review Lens

“Does this artifact align with leadership priorities, approval standards, and current strategy?”

Lens

AEO/GEO Lens

“Is your brand answer-ready for ChatGPT, Perplexity, Gemini, Claude, and AI Overviews?”

Lens

Competitive Lens

“What is the competitor strategy, what narrative are they winning, and where is the open lane?”

Lens

Records Governance Lens

“Is the output traceable, reviewable, retained, and exportable?”

Lens

Persona Lens

“How would a buyer, regulator, investor, journalist, employee, or competitor pressure-test this decision?”

Lens

Token Efficiency Lens

“Which workflows are wasting tokens, overusing models, or failing to reuse context?”

Output format

Every lens speaks the same language

Whatever the lens, the output schema is constant — so review is fast, comparison is possible, and nothing arrives without its evidence.

01Signal
02Interpretation
03Evidence
04Risk
05Recommended Action
06Confidence
07Source Trail
08Human Reviewer Options
Sample lens outputs

What a kit actually looks like

Yellow
Leadership Review Lens
Artifact: Market Research Brief: Healthcare Access Tool
Signal
The proposed research brief aligns with current strategic priorities but lacks a deployment pathway and measurable owner.
Interpretation
The asset is directionally aligned, but it may stall in leadership review because it reads as descriptive rather than operational.
Evidence
Priority memo, product roadmap, prior approved release, program owner notes.
Risk
Medium — approval delay and inconsistent framing.
Action
Add implementation pathway, success metric, owner, and 150-word executive summary.
Confidence
84%
Source trail
wiki://northstar/market-research-brief-healthcare-a · 6 linked sources · full provenance
Reviewer
High Priority
Competitive Lens
Artifact: Market Narrative Scan: Operational Efficiency
Signal
Atlas Civic is consolidating the operational efficiency narrative across AI answers and analyst language.
Interpretation
Your modernization proof points exist, but they are not structured as content the answer engines can quote.
Evidence
Prompt simulations, analyst excerpts, competitor product pages, trade coverage.
Risk
High — 60–90 day window before narrative hardens.
Action
Publish an operational modernization explainer, update executive language, add FAQ schema, and brief two analysts.
Confidence
82%
Source trail
wiki://northstar/market-narrative-scan-operational- · 6 linked sources · full provenance
Reviewer
Gap Detected
AEO/GEO Lens
Artifact: Answer Test: “How is Northstar different?”
Signal
AI engines answer “How is Northstar different?” with incomplete or competitor-led framing.
Interpretation
Entity clarity is strong, but source authority and answer consistency are lagging.
Evidence
Prompt test library, owned website crawl, competitor comparison, schema check.
Risk
Medium — prospective buyers receive inconsistent answers.
Action
Create a definitive differentiation page, update product FAQs, add structured proof points, monitor weekly.
Confidence
78%
Source trail
wiki://northstar/answer-test-how-is-northstar-diffe · 6 linked sources · full provenance
Reviewer
Optimize
Token Efficiency Lens
Artifact: Workflow Audit: Marketing & Strategy Prompts
Signal
Marketing and strategy teams repeat 61% of context across prompt runs.
Interpretation
The organization is paying models to re-read the same background instead of pulling a ready-made context package.
Evidence
Prompt logs, workflow audit, token spend by task, retrieval benchmark.
Risk
Medium — unnecessary cost and inconsistent outputs.
Action
Create reusable context packs for campaign review, competitor response, executive memo drafting, and AEO content updates.
Confidence
88%
Source trail
wiki://northstar/workflow-audit-marketing-strategy- · 6 linked sources · full provenance
Reviewer
Governed · Reusable · Auditable

Encode once. Apply everywhere.

Lenses are encoded once and reused across the entire wiki. Calibration is fast because the source-backed context already exists — there is nothing to re-gather, re-paste, or re-explain.

r you taking advantage?

Which question do you need answered first?

Pick a lens in week one. See your first kits by week three.

Request a PilotExplore the Personas