Think-it
Think-it is based in Berlin, Germany and works in Large Language Models for Climate Technology, with further work in Edge AI & IoT and Predictive Analytics.
- Average rating
- —
- Reviews
- 0
- Profile coverage
- 80%
- Evidence percentile
- P75
Profile updated · Request a correction
Company & commercials
- Primary category
- LLM Agents & RAG
- Team size
- Not disclosed
- Typical budget
- Not disclosed
- Primary industry
- Environmental & Sustainability Services
What Think-it does best.
LLM Agents & RAG provider for Environmental & Sustainability Services
Engineering collective building sustainable AI solutions including data spaces, LLM-enabled products, and AIOps through consulting and product development to drive socially responsible global digital impact. Its own website shows its strongest capability in Large Language Models within LLM Agents & RAG. The industry it describes most is Climate Technology.
4 platforms & methods
Bars show how many mapped capabilities use each one.
- AWS1 capability
- Terraform1 capability
- Kubernetes1 capability
- LLMs1 capability
Evidence report
How Think-it compares with peers on evidence, reviews and coverage.
What the evidence says
Think-it presents as a moderate evidence profile for LLM Agents & RAG. It ranks in the 75th percentile of 1,860 published providers in LLM Agents & RAG, and no reviews on the profile yet.
Current positioning: P75 evidence quality · P76 industry breadthAI capabilities.
AI Ethics & Governance
None of the listed technologies is specific to AI Ethics & Governance.
Mapping source · https://think-it.io/ — “solutions that scale . With a model-agnostic approach and a focus on responsible AI , we ensure technology serves its purpose while staying adaptable, et”
Featured 12 of 22 capabilities, ranked by mapping grade then confidence.
Industries served.
- Climate TechnologyDirect · Primary95%
https://think-it.io/ — “centric products. data sharing systems socially responsible products. climate technology. new frontier technology. responsible GenAI products health technolog”
- 90%
https://think-it.io/case-studies — “regulatory product milestones on a tight timeline Mapping rainforest biodiversity for XPRIZE teams We built sandbox environments with hard-to-access da”
- 80%
https://think-it.io/case-study/Carbon-removal-dMRV — “dMRV solution to empower tropical landowners in generating verifiable carbon credits and additional income through sustainable practices. Importance of Em”
- Circular EconomySupported60%
https://think-it.io/case-study/solving-for-scope-3-emissions-in-the-logistics-industry — “tics companies to share scope 3 emission data. Supply Chain/Logistics Climate Tech API Design Cloud Infrastructure Data Engineering Serverless Data Shar”
- Environmental ConsultingSupported60%
https://think-it.io/case-study/solving-for-scope-3-emissions-in-the-logistics-industry — “tics companies to share scope 3 emission data. Supply Chain/Logistics Climate Tech API Design Cloud Infrastructure Data Engineering Serverless Data Shar”
- Waste Management & RecyclingSupported60%
https://think-it.io/case-study/solving-for-scope-3-emissions-in-the-logistics-industry — “tics companies to share scope 3 emission data. Supply Chain/Logistics Climate Tech API Design Cloud Infrastructure Data Engineering Serverless Data Shar”
- Water Technology & TreatmentSupported60%
https://think-it.io/case-study/solving-for-scope-3-emissions-in-the-logistics-industry — “tics companies to share scope 3 emission data. Supply Chain/Logistics Climate Tech API Design Cloud Infrastructure Data Engineering Serverless Data Shar”
What clients say.
The partnership with Think-it has not only allowed us to rapidly scale the team but also maintain an excellent level of engineering.
Worked with Think-it? Review them → Every reviewer is verified by RankGlobal.
Sources behind this profile.
The RankGlobal Research Team opened each page and checked that it names Think-it. Pages on Think-it's own website are provider-supplied.
Case studies
- Scope 3 emissions data space for the logistics industryOn Think-it's website·checked 23 Oct 2026
- Digital tire diagnosis data infrastructure for the My BMW AppOn Think-it's website·checked 23 Oct 2026
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
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- Primary category
- LLM Agents & RAG
- Primary industry
- Environmental & Sustainability Services
- 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 Environmental & Sustainability Services — the strongest industry signal on this profile.
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