Making Sense

LLM Agents & RAG · AI Ethics & Governance · Automation & WorkflowPalo Alto, United States

Making Sense works in Retrieval-Augmented Generation for Critical Infrastructure Protection, with further work in Automation & Workflow and AI Ethics & Governance.

Average rating: —
Reviews: 0
Profile coverage: 70%
Evidence percentile: P51

Profile updated Oct 27, 2026 · Request a correction

AI Ethics & GovernanceAutomation & WorkflowComputer VisionLLM Agents & RAG4 categories

63Moderate evidenceStructured signal · 63/100

Primary category: LLM Agents & RAG
Team size: Not disclosed
Typical budget: Not disclosed
Primary industry: Government & Public Sector

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Overview

What Making Sense does best.

About

LLM Agents & RAG provider for Government & Public Sector

Its own website shows its strongest capability in Retrieval-Augmented Generation within LLM Agents & RAG, alongside Multi-Agent Systems and Tool-Using AI. The industry it describes most is Critical Infrastructure Protection.

Service model·Service

Primary AI categoryLLM Agents & RAG

Benchmarked against 1,860 providers in this category.

Primary industryGovernment & Public Sector

RankGlobal provider intelligence

Evidence report

How Making Sense compares with peers on evidence, reviews and coverage.

Analyst brief · Published

CategoryLLM Agents & RAG

Compared with1,860 providers

Signals3 signals

Status● Published

Evidence score

63/100

Moderate evidence51st percentile of 1,860 peers · peer median 70

Profile coverage70

Taxonomy density90

Review signal0

Peer benchmarkHow the profile comparesLLM Agents & RAG among 1,860 published providers

Average rating0.00 · median 4.89

Independent reviews0 · median 0

Profile completeness70% · median 70%

Taxonomy breadth18 · median 20

This profile Peer median

Signal radarMulti-dimensional evidence

This profile (percentile) Peer median

Industries2 industries

2industries

Financial Services & Insurance50%

Government & Public Sector50%

Share of mapped industries, not share of work or revenue.

Evidence mixMapping grades

Direct · 18

100%Direct · 18 mappings

Grades across 18 mappings. Not a search ranking.

Analyst summary

What the evidence says

Making Sense presents as a moderate evidence profile for LLM Agents & RAG. It ranks in the 51st percentile of 1,860 published providers in LLM Agents & RAG, and no reviews on the profile yet.

Current positioning: P51 evidence quality · P44 industry breadth

Strongest signalsEvidence-backed strength in LLM Agents & RAG is the profile's clearest signal in the mapped taxonomy.

Best user fitGovernment & Public Sector buyers evaluating LLM Agents & RAG across engagement sizes.

Confirm before engagementConfirm current delivery capacity directly — mapped signals reflect profile evidence, not live availability.

How this report is calculated →

Capabilities

AI capabilities.

AI category · 1 / 12

AI Ethics & Governance

—

DirectSupportedRelatedAdjacentOne of 934 providers in this category

Compare AI Ethics & Governance providers →

Technology used

None of the listed technologies is specific to AI Ethics & Governance.

Mapping source · https://makingsense.com/technology-advisory/ai-adoption-enablement — “7;s a clear baseline and progress is visible throughout. How to build AI governance in a company? Making Sense builds governance as part of the program,”

Featured 12 of 16 capabilities, ranked by mapping grade then confidence.

Industry experience · 2 industries · 2 subindustries

Industries served.

2 Core0 Adjacent · discovery only

Government & Public SectorOther providers in Government & Public Sector →

Critical Infrastructure ProtectionDirect · Primary
95%
https://makingsense.com/technology-advisory

Client feedback

What clients say.

No independent reviews found for Making Sense yet.

Worked with Making Sense? Review them → Every reviewer is verified by RankGlobal.

Methodology

How RankGlobal maps this profile.

RankGlobal maps this profile against a controlled taxonomy. Mapping grades on capability and industry cards describe how the profile is classified. Source strength for ranking decisions follows the hierarchy published on Research — a mapping grade is not a claim of discoverability weight.

T1AuthoritativeTypical evidenceRegulators, registries, certifications, signed client evidence.Scoring useHighest evidentiary weight
T2IndependentTypical evidenceCredible media, industry bodies, partner directories, third-party datasets.Scoring useStrong with attribution and recency
T3Provider-controlledTypical evidenceCompany site, case studies, press releases, structured submissions.Scoring useAccepted as a claim; verification raises weight
T4Discovery-onlyTypical evidenceDirectory listings, aggregations, and early discovery signals.Scoring useUsed for discovery; weighted accordingly in ranking

Direct, Supported, Related and Adjacent appear on mapped cards as classification grades. They do not rank how discoverable a provider should be.RankGlobal trust center →

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Before you reach outKey facts, and three things to confirm once you're in touch.

Primary category: LLM Agents & RAG
Primary industry: Government & Public Sector
Typical budget: Not disclosed
Team size: Not disclosed

1Name the use caseSay which LLM Agents & RAG problem you are evaluating, so the research team can route your message accurately.
2Pressure-test the budget bandNo budget band is on file. Ask what a scope like yours typically lands at.
3Ask for a referenceRequest a client reference in Government & Public Sector — the strongest industry signal on this profile.