CLIMATE FINANCE INTELLIGENCE

Knowledge Management for Climate Finance

Built specifically for teams developing climate finance proposals, Climate Finance Intelligence turns static documents both internal and external into an instantly searchable knowledge base, delivering critical insights and donor alignment in seconds, not weeks.

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"Integrating this software into our workflow means we can deliver superior quality proposals faster. This isn’t about replacing expertise; it’s about amplifying it, allowing our team to be more strategic and effective in this industry."

Qavah Earth Cape Town

"I found your AI assistants very helpful not only in organizing ideas, aligning them with GCF criteria and bringing in persuasive language but it dropped the less useful parts. Most importantly, it saved loads of time."

Int'l Delivery Partner Africa

"Accessing the latest GCF format updates is a major challenge. The Concept Note Converter has been an invaluable resource that bridges this gap, ensuring our Concept Notes were aligned with the latest GCF standards."

Project Proponent Zimbabwe

"The ability to rapidly evaluate a concept note against GCF criteria is a game-changer. It saved us days of work and allowed us to deliver a superior product to our clients at a fraction of the traditional cost, which was a huge win for both sides."

Project Developer South Africa

"It would be wise to have Concept Note Evaluator in the initial assessment of concepts and in the final stage as well. Useful for project developers, private players and GCF climate finance applicants with limited GCF application experience."

Development Bank Southern Africa

"The Converter tool was a lifesaver, migrating our Concept Note to the new GCF format in under two hours. The summary of changes was especially insightful, providing a rationale that would have taken us days of research."

Project Proponent Africa

The stakes are high: General-purpose AI isn't built for this

Generic AI infers answers from the open web - hallucinations, no traceability, and an agreeable streak that hands you whatever case your prompt implied. CFI is anchored to documents you own or are authorized to use. Every finding is tied to verifiable source text, with an emphasis on critical evaluation over affirmation.

Built On Your Own Files

CFI is populated with the materials you own or are authorized to use: your past submissions, technical notes, and the external sources you select. It is a strictly private - your dataset is never shared and never used to train AI models.

Every Insight Is Cited

Each response traces to specific source text. Built-in references let you verify exactly where a finding comes from - not inferred, not paraphrased, not invented.

Critical In Evaluation

The platform can only draw on what's in your dataset, so it cannot manufacture support that isn't there. The assistants are configured to evaluate critically rather than just agree.

The intelligence behind the platform

Climate Finance Intelligence is built on three powerful layers designed to rapidly deliver precise insights across a wide range of complex and analytical questions. 

ONE QUESTION, ALL 3 LAYERS

An Accredited Entity Analyst asks:

"We're preparing an ecosystem-based adaptation proposal for a strategic water-source area - what have we done before, what has the GCF approved, and what's the climate evidence?"

CFI Returns In Seconds:

  • The entity's prior EBA projects in comparable water-source areas, with results and lessons learned.
  • Comparable GCF-approved adaptation proposals with theory of change and co-financing.
  • The peer-reviewed climate evidence most cited in approved water-security proposals.
  • Layer 1: Institutional Layer

    The institutional layer activates an organization's internal history by indexing previous submissions and internal technical notes. This prevents the loss of institutional memory when staff rotate or external consultants move on from a project.

  • Layer 2: Climate Science Layer

    This layer integrates authoritative global and regional climate data. The base layer is comprised of reports and publications most cited in approved project files. It directly supports the construction of a defensible climate rationale.

  • Layer 3: Donor Layer

    On behalf of our clients, we can integrate the publicly available project libraries of most donors. Thousands of project files, including Concept Notes, Funding Proposals and more - searchable by your team.

Step 1: Select a Theme-Based Prompt or Enter Your Own Question

After creating your CFI account, select a theme and explore example prompts in the main screen or prompt library. Choose a prompt, update the fields if needed and click submit or enter your own question.

Step 2: Review the Output & Sources

Once you've submitted your prompt or question, in a few seconds a generated output with verifiable source citations will display. Review the output and feel free to continue the conversation by asking follow-up questions to refine the results.

 

HOW IT WORKS

The Knowledge Vault

Don't just guess - build. Instantly access proven models, logic and arguments from thousands of approved project files to strengthen and align your submissions. 

 

YOUR THREE STAGE CFI PATHWAY

Built for you. Mastered by your team. Proven in practice.

A three-stage pathway designed to deploy your custom CFI instance fast, onboard your team smoothly, and provide ongoing performance support.

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STAGE 1: BUILD + DEPLOY

Platform Deployment

Janus builds customized version of CFI.

  • Custom knowledge layers (donor files, climate science, institutional knowledge)
  • AI Assistants for CN, FP and special tasks
  • Self-hosting option with Master Admin Panel
  • Data security: localization options and more
  • Full data portability - client owned
  • OUTCOME: A customized instance, deployed and operational on Janus or your own cloud infrastructure.

STAGE 2: UPSKILLING

Onboarding

2-3 onsite engagements/demos.

  • Introduces team to the CFI environment
  • Familiarization of Knowledge Discovery Ops (Knowledge Vault)
  • Familiarization using the Assistants
  • Exercises: Trainer led exercises to enable proficiency in using all capabilities
  • OUTCOME: A team that is proficient and confident using the platform.

STAGE 3: PERFORMANCE

Performing

Ongoing performance with Janus.

  • Efficiency: A major reduction in labor spent on climate research
  • Insights: Team rapidly distills insights & lessons learned from knowledge layers
  • Alignment: More donor aligned CNs and FPs - reducing revision cycles
  • Assured: Data security and compliance with all data safeguarding
  • OUTCOME: Significantly elevated success in unlocking climate finance.

Stress-test every Concept Note and Funding Proposal

Beyond knowledge discovery, CFI includes specialized AI assistants that add speed and precision for quality assurance. Each can be customized to your enterprise instance.

Concept Note Evaluator

This assistant provides a criterion-by-criterion evaluation of every section of your Concept Note, benchmarked against donor precedents. It identifies missing elements, highlights areas for strengthening, and suggests the most effective winning arguments.

Funding Proposal Evaluator

Applies a three-layer methodology to check for document compliance, investment quality, and alignment with precedents from similar projects. It identifies missing elements, highlights areas for strengthening, and offers alternative language where needed.

Climate Rationale Advisor

Build a robust evidence-based justification for your project. This assistant anchors your climate rationale in the latest scientific data and expresses your specific climate rationale claims in alignment with proven precedents.

Concept Note Drafter

Resolve the blank space problem by leveraging this assistant to generate a first draft of your Concept Note. By synthesizing your project idea with core inputs, this tool generates a high-quality baseline that you can refine.

Theory of Change

Construct a logical, donor-aligned Theory of Change (ToC). This assistant helps you map inputs, activities, and outputs to long-term climate impacts, ensuring your causal pathways are similar to successful logic models.

Project Preparation Facility

This assistant guides you through drafting a PPF application, identifying the specific feasibility studies and expert inputs required by donors and generates the specific language needed.

Data Security: Your Data, always secure

Your  “instance” runs on dedicated infrastructure, never shared with other clients. Your proprietary documents are kept strictly confidential, are never used to train AI models, and remain fully portable and client-owned. Where general-purpose AI tools retain and learn from what you feed them, CFI is built the opposite way.

Dedicated and Private

Your CFI instance runs on dedicated infrastructure with no shared servers and no co-mingling with other clients. Data is encrypted in transit and at rest, behind firewall and network-level access controls.

Zero Retention In Writing

Prompts and session data are processed in-memory, then permanently discarded - never logged, stored, or used to train any model. This is backed by a formal, written exception from our AI processor.

Your Data to Keep

Your documents are never used to train AI models and never leave your control. Hosting can be Janus-managed or migrated to your own infrastructure, and your full dataset stays portable and client-owned.

FAQs

We’ve covered the most frequently asked questions below. If you have any additional questions, contact us at anytime. 

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CFI is a specialist enterprise platform, not a general-purpose chatbot. Key differences:

  • Single-tenant architecture: Your instance is dedicated to your organization. No shared infrastructure with other clients.
  • Three integrated knowledge layers: CFI searches across 3,000+ approved GCF project files, 100+ authoritative climate science publications, and your own institutional documents simultaneously. Commercial AI tools have none of this.
  • Zero-retention architecture: No prompt or session data is retained or logged after a query completes. Commercial AI tools retain and may train on your data.
  • Agentic AI assistants: Purpose-built assistants evaluate Concept Notes and Funding Proposals against donor criteria and scoring guidance. Commercial AI cannot replicate institutional knowledge of GCF evaluation standards.
  • Institutional memory: CFI retains and compounds knowledge across staff rotations and consultant departures. Commercial AI starts from zero every session.

CFI operates on a zero-retention architecture — no prompt or session data is retained or logged after a query completes. All data is processed strictly in-memory to generate a response and then permanently discarded. No human review occurs, and no data is used for model training. The platform is hosted on dedicated VPS infrastructure in a certified German data centre with AES-256 encryption at rest and TLS 1.2+ encryption in transit. Each client operates on a dedicated instance — no shared infrastructure with other clients. Google has granted Janus a formal, written exception to its standard prompt logging policy, ensuring zero retention at the AI inference layer as well. Self-hosting on your own cloud infrastructure is also available.

CFI is delivered as a professional services engagement, not a software subscription. Enterprise pricing is estimated at $25,000 USD per year, structured across a four-year engagement period — a total programme cost of $100,000 USD. The client retains full ownership of all configured tools, knowledge layers, and documentation throughout and beyond the engagement. On-demand analytical services — such as individual Concept Note evaluations and co-financing benchmarks — are available separately and independently of the enterprise engagement.

Yes. CFI is positioned as an institutional capacity-strengthening activity under GCF Readiness and Preparatory Support funding. GCF's own Readiness Guidebooks explicitly fund digital Knowledge Management Systems for Direct Access Entities, and CFI is purpose-built to meet those requirements. Several Accredited Entities are currently incorporating CFI into their readiness proposals.

CFI integrates three knowledge layers:

  • Layer 1 - Donor Knowledge: The complete approved GCF corpus, indexing over 3,000 project files including Concept Notes, Funding Proposals, PPF applications, Board decisions, and framework papers.
  • Layer 2 - Climate Science: Approximately 100+ verified open-access publications from the most authoritative bodies in the field (IPCC, World Bank, AfDB, UNEP, WMO, WHO) — the sources most frequently cited in approved GCF submissions.
  • Layer 3 - Institutional Knowledge: Your organization's own submission history, internal technical notes, and project files — preventing the loss of institutional memory when staff rotate or consultants depart.

One query searches all three layers simultaneously.

The platform's donor knowledge layer is built on the complete GCF corpus, and coverage extends to the Adaptation Fund and GEF. AI assistants are calibrated to GCF and Adaptation Fund submission standards. Additional donor knowledge layers — such as AfDB, EIB, World Bank, and bilateral climate funds — are available on a separately scoped basis.

No. CFI does not generate AI content on behalf of clients for submission to the Secretariat. It provides evidence-based intelligence and quality assurance to support your own preparation and review processes. The platform empowers your team with the knowledge and benchmarks to produce stronger submissions — the drafting and decision-making remain with your team.

CFI includes task-specific agentic AI assistants configured and delivered as part of the professional services engagement:

  • Primary Insights Search: Surfaces comparable approved projects with their theory of change, co-financing structure, and design features.
  • First Draft CN Builder: Produces a structured first-draft Concept Note aligned to GCF or AF templates, anchored in approved precedent.
  • Concept Note Reviewer: Stress-tests a draft CN against comparable approved CNs, flagging gaps in climate rationale, theory of change, and investment criteria.
  • Funding Proposal Reviewer: Section-by-section audit of any FP against the full corpus, ranking corrective actions by scoring impact.
  • GCF Reviewer Response Assistant: When the Secretariat sends review comments, surfaces how comparable approved proposals addressed the same issues.

The platform also includes several hundred pre-built prompts for Environmental and Social Safeguards (ESS) and Monitoring, Evaluation, Accountability and Learning (MEAL) workflows.

CFI uses a Retrieval-Augmented Generation (RAG) architecture that grounds every response in curated, verified source documents. Responses cite specific approved projects and publications from the knowledge layers — not generated text. AI assistants are configured with constrained output structures and evaluation criteria drawn directly from donor guidance. This architecture significantly reduces the hallucination risk associated with general-purpose AI tools. The human-in-the-loop approach ensures that domain experts review and act on insights, not raw AI output.

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Ready to see Climate Finance Intelligence in action? Book a demo today to see how it can solve all of your climate finance bottlenecks and use cases.