Decision infrastructure for African opportunity programs.
From intake to donor reporting, FairLens runs the whole arc for foundations, fellowships, and grant programs across Nigeria and Africa.
Total Applications
2,847
Under Review
423
Fairness Score
96.2%
Fairness score across 2,847 evaluations
Built and validated with leading institutions
Selection programmes break at scale.
Past a few hundred applications, the same review process that worked for fifty starts producing rushed reads, inconsistent calls, and applicants who never hear back. None of this is anyone's fault. It's the predictable consequence of trying to do careful work at volume without the right machinery.
73%
of reviewers report burnout
Review doesn't scale
Past a few hundred applications, the same reviewer is reading shallower than they were on application one. Decisions get made on volume, not merit.
2.4x
variance across reviewers
Inconsistent judgment
Two reviewers reading the same packet often disagree by more than a point. Without a shared rubric, the same applicant gets a different answer depending on who picked up the file.
68%
influenced by irrelevant factors
Hidden bias
Institution names, geography, gendered language in essays. Without a structured rubric and after-the-fact analysis, the bias is there and invisible. You can't fix what you can't see.
89%
receive zero feedback
Applicant frustration
After weeks of effort, the applicant gets a one-line rejection. Even a good decision feels untrustworthy when nobody can say why.
3x
increase in audit challenges
Compliance risk
When a rejected applicant escalates, you need a paper trail older than 'we discussed it.' Decisions without an audit record expose the institution to reputational and regulatory risk.
How a cycle runs.
One programme, five stages. Design the programme, collect applications, let the AI read and structure them, give reviewers an evidence-linked view, and (if you want) wire the whole thing into your own systems through the API.
Design the programme
Build the application form, define evaluation criteria with AI assistance, and set fairness controls. Programme builder, one place.
AI Criteria Assistant helps you define what 'strong,' 'adequate,' and 'weak' look like for your programme.
Collect applications
Applicants submit through a mobile-friendly form with auto-save and progress tracking. They know what's being asked and when they'll hear back.
Clear requirements. Guided completion. Dignity-first design.
AI reads and structures
The AI engine processes every submission into structured, citation-grounded signals. Each score points back to the page or paragraph that justified it.
Transparent signals, not opaque scores. Every assessment ties back to source.
Humans decide
Reviewers get a summary, a criterion-by-criterion breakdown, and the evidence citations. They decide faster, with less fatigue, and more consistently than reading PDFs cold.
When a reviewer disagrees with the AI, the override is logged with the reason. Auditable later.
Headless API
Submit applications, fetch evidence-grounded scores, and stream reviewer feedback through a documented REST API. Drop FairLens behind your own UI, or pipe decisions into downstream systems.
OpenAPI 3.1 + Bearer auth. Sandbox with deterministic synthetic data.
The whole arc, in one system of record.
Most platforms stop at the decision. FairLens runs the cycle end-to-end, so the same applicant ID carries from the application form to the donor’s board pack. The evidence trail comes with it.
Intake to decision
Receive applications, score them against your rubric with evidence on every line, calibrate reviewers, and decide.
- Public application forms
- Evidence upload & integrity checks
- AI scoring against your rubric
- Gold-set calibration
- Reviewer assignment & comparison
- Bias monitoring across cohorts
Decision to disbursement
Move from a finalised decision to a notified, paid, and onboarded recipient, with the audit trail attached.
- Decision workflows & overrides
- Award letters & applicant comms
- Public discover page for programs
- Payments via Stripe & Paystack
- Per-decision audit log
Award to outcome
Follow the people you funded for as long as you fund them. The same applicant ID carries through to outcome data and the donor report.
- Beneficiary self-service portal
- Scheduled check-ins & nudges
- Outcome tracking at 6 / 12 / 24 months
- Cohort engagement quality
- Donor-grade PDF reports
- Fairness reports per cohort
Seven commitments we hold ourselves to.
These aren't marketing slogans. They're product-architecture decisions that constrain what we build, and how we build it. When something we ship contradicts one of these, we go back and fix the thing we shipped.
Human Accountability Always
AI recommends, humans decide. Every decision has a responsible person.
Transparency Over Convenience
Every AI output must be explainable. No hidden scores or opaque logic.
Fairness Before Speed
We optimize for equitable outcomes, not just processing velocity.
Consent Before Collection
No data is gathered without clear purpose and applicant awareness.
Learning Over Punishment
Rejection becomes growth through constructive, personalized feedback.
Structure Over Intuition
Explicit criteria beat gut feelings for consistent, defensible decisions.
Dignity for Applicants
Applicants are people investing hope and effort, not data points to process.
Three roles, one platform.
Programme organisers, reviewers, and applicants each see a different view of the same underlying decision record. The copy below is how the product feels to each of them, not a stakeholder map.
Programme Organizer
Institutions, teams, or individuals designing and running selection programs.
Goals
- Design fair, clear programs faster
- Evaluate many applicants consistently
- Defend decisions if challenged
Pain Points Today
- Overwhelming submission volume
- Inconsistent reviewer judgment
- Limited insight into decisions
AI Copilot Role
A thinking partner for programme design. It suggests, you decide.
Reviewer
Panel members, assessors, faculty, recruiters, or subject matter experts.
Goals
- Understand applicants quickly and fairly
- Make confident decisions
- Justify decisions clearly
Pain Points Today
- Information overload & time pressure
- Unclear criteria
- Emotional fatigue from volume
AI Copilot Role
An analyst that summarises, highlights, and explains. It never makes the call.
Applicant
Students, professionals, or individuals seeking access to programs, roles, or resources.
Goals
- Understand what is being asked
- Present themselves clearly
- Receive feedback and closure
Pain Points Today
- Opaque requirements and evaluation logic
- Silence after submission
- Feeling judged on irrelevant factors
AI Copilot Role
Clear requirements upfront. Honest feedback after. Applicants know where they stand.
Built for African opportunity programs
High-stakes selection looks the same wherever it runs across the continent: multiple reviewers, high volume, reputation-sensitive outcomes. One platform, four flavours of the same problem.
Scholarships & Bursaries
Fair financial-aid selection for African foundations and university programmes. Transparent criteria, evidence-linked scoring, and a written reason every applicant can read.
Fellowships & Awards
Run continent-spanning fellowship cycles with calibrated peer review, consistent rubrics, and audit trails reviewers and funders can defend.
Accelerators & Incubators
Surface high-potential African founders with structured evaluation that cuts through prestige bias and halo effects across hundreds of applications.
Grants & Funding
Evaluate proposals consistently across public, private, and NGO grant programmes in African markets. Every score is anchored to a passage in the proposal.
Swipe to explore
Pay-as-you-go credits
One-time credit packs. No subscription. Each AI evaluation, criteria extraction, or applicant feedback consumes credits, and you buy more when you need them. Foundations running recurring large-scale cycles usually want an annual programme plan instead. Talk to us.
Starter
Pilot a program. Evaluate up to ~20 full applications.
- 100 evaluation credits
- 1 active program
- All AI features included
- Email support
- Credits never expire
Growth
Most PopularFor programs at hundreds of applications per cycle.
- 1,000 evaluation credits
- Unlimited programs
- Bulk import
- Calibration tools
- Applicant feedback
- Priority support
Scale
For institutions running multi-cohort cycles a year.
- 10,000 evaluation credits
- Everything in Growth
- Custom branding
- Anonymization controls
- Dedicated onboarding
Enterprise
Annual program plan for foundations running recurring multi-cohort cycles.
- Annual credit allocation for recurring cohorts
- Donor-impact and fairness-audit reporting for funders and boards
- Data residency + NDPR/POPIA/Kenya DPA/Ghana DPA alignment
- Dedicated onboarding, reviewer training, and unlimited reviewer seats
- SLA guarantee
- SSO and advanced security
- Custom API and integrations
Credits never expire. Top up any time. A typical full evaluation (document + scoring + feedback) costs 5–8 credits.
What Program Leaders Say
Pilot complete. Young Talent Programme 2026, ~2,800 applications evaluated. Full quote and case study coming soon.
Lagos Business School
Partnership in progress. Public quote and case study to follow once the pilot is underway.
Pan-Atlantic University
Pauses on hover · swipe or drag to browse
Run your next cohort on FairLens.
Set up your programme in an afternoon. Bring your reviewers in for the next cohort. Keep the audit trail for the board meeting after.
Pay-as-you-go credits. No subscription. Setup in under 30 minutes.