Revenue rank on Toolify.
← AI Revenue Radar · Toolify Top 300
Kive
AI-powered platform for creative collaboration, visual asset management, and brand consistency.
Market Data Board
371.7K monthly avgRead the market signal first
Traffic and channel data use SimilarWeb methodology; keyword metrics come from DataForSEO; ranking and revenue signals come from Toolify. Evidence snapshot 2026-07-06.Estimated monthly traffic (directional, not audited revenue).
Primary market category.
Non-brand search share indicates how much task-led discovery may exist.
Channel mix share of visits
Top countries traffic share
Competitor traffic three-month visits
Keyword Evidence
5 keywordsTask-keyword opportunity table
Score is Shipsite's opportunity score, blending the metrics on the left. Auditable inputs are Volume, KD, CPC, allintitle and KGR.| Keyword | Volume | KD | CPC | KGR | Score |
|---|---|---|---|---|---|
| kive | 1.9K | 11 | $6.2 | — | 78.8 |
| moodboard maker | 3.6K | 21 | $2.64 | — | 60.7 |
| dam for creative teams | — | — | — | — | 0 |
| ai image tagging library | — | — | — | — | 0 |
| kive alternative | — | — | — | — | 0 |
KGR is shown once allintitle sampling lands for a keyword; Volume, KD and CPC are already auditable.
Product Evidence
0 capturesProduct and pricing captures
Only the product's own public pages are shown here.No public product screenshots passed the current evidence gate.
Strategy Frameworks
Business canvases and strategic analysis
Thirteen grounded views aligned with the site-building strategy desk: Business Model Canvas, Value Proposition Canvas, JTBD, ICP, Empathy Map, Customer Journey, SWOT, PESTAL, Porter's Five Forces, 3C, STP, 4P and AIDMA — opened by the insight brief.One-line positioning
Kive pairs AI-tagged asset library with moodboard collaboration for creative teams.
Target user
Designers organizing assets, collaborating on moodboards, billed via team subscription.
Category role
AI-tagged DAM: a niche asset-management role in design tooling, not a general canvas.
THE VERDICTKive survives on direct traffic and AI-tagging differentiation, but Figma's free tier marginalizes it in its core US market.
Non-obvious insights
- 68.5% Direct traffic plus 1,900 'kive' searches shows most visits are bookmarked repeat users, not new discovery.
- US traffic (29%) with USD pricing meets Figma's 700x-larger visits, meaning Kive fights free Figma in its own core market.
- getpoppy.ai's 835K visits already exceed Kive's 371.7K, showing Kive trails similarly scaled rivals.
Mechanisms worth studying
- Proves a narrow AI-tagging-plus-collaboration bundle can survive on direct traffic amid giants.
- Exposes the niche ceiling: trailing similarly sized getpoppy.ai shows sub-category capacity is limited.
01 · Business Model Canvas
Business Model Canvas
- Stripe is the payment infrastructure partner.
- Unknown; evidence shows no integration with platforms like Canva/Figma.
- Unknown; evidence provides no investor or strategic-partner info.
- Direct Stripe integration means Kive owns tax compliance itself, not via an MoR.
- Ongoing development of AI-tagging and moodboard-collaboration features.
- Unknown; evidence doesn't describe content moderation or quality control.
- Acquiring users via self-service conversion and SEO content reaching designers.
- 68.5% direct traffic implies marketing rides on designer word-of-mouth, not SEM spend.
- Asset copyright provenance needs human review; AI tagging can't replace that judgment.
- Core value: AI-tagged asset library plus moodboard collaboration, used via team seats.
- Pricing: limited free tier plus Pro at ~$12-24/seat/month, a lightweight subscription.
- Unknown; evidence has no data on emotional or social validation for users.
- Unknown; evidence has no trial-conversion, reliability, or experience-risk data.
- AI auto-tagging differentiates it; it sits near Canva/Figma but at far smaller scale.
- Self-service, team-seat subscription; no evidence of a dedicated success team.
- Unknown; evidence doesn't describe support channels or service form.
- Unknown; evidence provides no retention, renewal, or churn data.
- Unknown; evidence includes no reviews, certifications, or compliance info.
- End users need to search, tag, organize assets, and arrange them into moodboards.
- Buyer/seat-admin role unspecified; evidence only shows billing per design team.
- Context: design teams managing an asset library and building moodboards for comparison.
- Pain: hard to search/tag assets. Gain: AI auto-tagging plus unified collaboration.
- Unknown; no LTV, retention, or team-size data given to quantify commercial value.
- AI-tagging algorithms and asset-library data structure are the core tech resources.
- 371.7K monthly visits with 68.5% Direct traffic show a returning-user base.
- Unknown; evidence gives no team size or funding info.
- Only 371.7K monthly visits at rank 249 make it a niche, mid-tier creative-tools player.
- AI auto-tagging needs ongoing image-recognition compute and scalable asset storage.
- Direct (68.5%) dwarfs organic search (9.97%); acquisition rides on brand recall, not content.
- Direct is the dominant channel at 68.5%; Organic Search adds nearly 10%.
- Transactions are self-service on the site, using Stripe as payment infrastructure.
- Delivered as a web app covering asset library, moodboard, and team-seat entry points.
- Unknown; evidence doesn't describe post-sale service or success channels.
- Ongoing R&D investment in AI-tagging models and collaboration features.
- Variable costs from image storage, AI inference, and asset processing.
- Unknown; evidence gives no data on support/operations team size.
- Organic + Paid Search at ~19% implies SEO and paid-search acquisition spend.
- Per-seat billing on direct Stripe means building multi-currency tax handling as customers grow.
- Billed per team-seat subscription, Pro roughly $12-24/seat/month.
- The free-to-Pro upgrade path forms expansion revenue.
- Unknown; no evidence of enterprise, API, or other revenue streams.
- No evidence of ad or data-licensing revenue; the only path is growing seat count.
02 · Value Proposition Canvas
Value Proposition Canvas
Product side · Value Map
- An AI-tagged asset library that auto-generates searchable labels for uploads.
- A moodboard module where team seats jointly arrange and discuss visual assets.
- Auto-tagging replaces manual categorization memory, relieving guesswork search.
- Moodboard collaboration pulls scattered discussion into one space, easing feedback loss.
- The image-recognition model continuously tags assets, creating retrieval-efficiency gain.
- Seat-based moodboards leave a collaboration trail, creating a traceable-review gain.
Customer side · Customer Profile
- Let everyone on the team quickly find and reuse the correct asset version.
- Avoid the irritation of repeatedly asking in chat where an image went.
- Without unified tagging, search depends entirely on remembering folder paths.
- Moodboard discussions scatter across chat tools, making feedback hard to retain.
- AI auto-tagging spares the repetitive labor of manually categorizing each asset.
- A unified moodboard space keeps review feedback centralized and traceable.
03 · JTBD
Jobs To Be Done
- When Designers and creative team members stall on creative teams, they search 'moodboard maker' or open kive.ai.
- Direct is 68.51% of observed visits, so 'moodboard maker' is a repeatable creative teams situation rather than a one-off search.
- Measured demand for 'moodboard maker' shows Kive is needed because the current stack cannot finish creative teams in one pass.
- A procurement window and seat budget force Design/creative team lead to choose Kive for 'moodboard maker' or an alternative now.
- The functional job is delivering usable creative teams in-session, not learning another full suite.
- Before paying, buyers still line up 'dam for creative teams' quality, limits, and Pro on one comparison sheet.
- Designers and creative team members want less panic after a failed creative teams pass, especially when 'moodboard maker' misses the expected result.
- Budget owners want proof the Stripe bill for 'moodboard maker' will not jump next cycle.
- Designers and creative team members want to look able to finish creative teams in front of peers, not still googling 'moodboard maker'.
- Proving to management that picking Kive for 'moodboard maker' was not a random tool buy is the social job.
- Success is a pasteable, shareable, or editable creative teams result inside the same session.
- It also means holding 'dam for creative teams' time, quality, and Pro inside a range Design/creative team lead can explain.
04 · ICP
Ideal Customer Profile
- The core profile is Designers and creative team members doing creative teams, in the AI-tagged digital asset management (DAM) category.
- Design/creative team lead pay for 'moodboard maker', and administration may sit with Team workspace admin.
- The buying trigger often shows up as a search for 'moodboard maker', already present in the audited keyword table.
- United States is 29.05% of visits, so local work seasons can turn 'moodboard maker' from latent need into a same-week must-solve.
- The primary pain is that creative teams is slow and error-prone, which is why 'dam for creative teams' exists as a task query.
- Seat quotes and usage swings make Design/creative team lead hesitate after the first 'moodboard maker' result.
- Budget signal for 'moodboard maker': Pro; observed rail is Stripe.
- Enterprise can buy seats or a contract for 'moodboard maker'; 371.7K traffic shows people already pay or keep trying.
- Decision criteria include 'moodboard maker' sample quality, limits, and whether Stripe checkout is frictionless.
- They also shortlist canva.com against 'moodboard maker', and trust hinges on whether official pricing is self-serve readable.
- The repeatable reach path for 'moodboard maker' buyers is Direct (68.51%), not a one-off campaign.
- The task query 'moodboard maker' plus kive.ai is the second touch, better for content pages than brand ads alone.
- Casual free-only users with no seat budget and no 'moodboard maker' job are outside Kive's primary ICP.
- People who use canva.com for a different job than 'moodboard maker' are not same-budget buyers.
05 · Empathy Map
Customer Empathy Map
Primary personaA design lead managing a studio's shared asset library and running moodboard reviews.
- They keep seeing 'moodboard maker' result pages, kive.ai, and same-job generation UIs.
- The comparison set keeps canva.com next to the incumbent 'moodboard maker' tool.
- Peers talk in queries like 'moodboard maker' and 'dam for creative teams', not official handbook language.
- Users in United States also hear whether 'moodboard maker' is worth the Stripe quota, not brand slogans.
- "moodboard maker" — searching for a tool to build visual boards.
- "dam for creative teams" — looking for asset management built for creative teams.
- Searches 'ai image tagging library' to compare auto-tagging tools.
- Uploads existing assets to test tagging accuracy before upgrading to Pro.
- "With assets piling up, folder naming alone can't surface the image I need.".
- "The team passes images around in chat during reviews — we need one shared space.".
- Feels worn out by repeatedly organizing assets by hand.
- Feels delighted and understood when AI tagging accurately identifies assets.
- They fear having to redo a failed creative teams pass; searching 'moodboard maker' is already a frustration signal.
- Unclear bills or seats on 'moodboard maker' makes lock-in to Kive feel hard to admit.
- The ideal gain is finishing creative teams in-session and handing over an output that satisfies 'dam for creative teams'.
- If Direct can find Kive again for 'moodboard maker' (68.51%), a successful reuse becomes habit instead of another bake-off.
06 · Journey Map
Customer Journey Map
Discover01
Evaluate02
Onboard03
Retain04
Advocate05
Emotion curve (inferred)
Key behavior
Discovers Kive through design searches like 'moodboard maker'.
Compares against Figma/Canva to weigh if dedicated tagging is worth a separate fee.
Uses the limited free tier to upload assets and test AI-tagging results.
The team keeps using moodboard collaboration for ongoing review meetings.
Mentions Kive when sharing DAM tool recommendations in design communities.
Friction / drop-off
'moodboard maker' gets 3,600 searches but competes with the brand term, limiting entry.
Figma's visits are nearly 700x Kive's, easily pulling users back to the free platform.
The limited free quota can be exhausted in one batch for teams with large libraries.
The narrow scope falls short once a team's needs expand into broader workflows.
With getpoppy.ai similarly sized, referrers may steer people to compare instead.
Product lever
The branded term 'kive' draws 1,900 searches, showing discovery beyond pure SEO.
AI tagging is the key argument that Figma's generic collaboration isn't enough.
The limited free tier lets teams validate tagging accuracy before paying.
Moodboard collaboration anchors review meetings inside Kive, building stickiness.
No affiliate/referral incentive evidence; advocacy relies on organic design-community talk.
07 · SWOT
SWOT Matrix
- AI tagging forms a differentiated labeling capability versus peer DAM tools.
- 68.5% direct traffic reflects an established base of brand-loyal repeat visitors.
- A notable share from high-income Hong Kong/UK regions gives seat-payment capacity.
- Narrow scope limits breadth versus feature-rich rivals like Figma.
- Low pricing ($12-24/seat) implies a limited revenue ceiling per customer.
- 68.5% Direct concentration shows little evidence of channel diversification.
- "moodboard maker" has 3,600 monthly searches at KD 21 — low-competition SEO upside.
- Canva/Figma's huge user base could spill over into a specialized DAM tool.
- Hong Kong + UK traffic over 12% combined suggests international expansion potential.
- Large platforms like Canva/Figma could add AI-tagging features, eroding differentiation.
- Similar tools like getpoppy.ai indicate rising competition in this niche.
- Unknown funding status; if underfunded, it may struggle against resource-rich rivals.
08 · PESTAL
PESTAL Macro Environment
- The EU AI Act may impose transparency-disclosure duties on automated image-classification systems.
- Unsettled US Copyright Office policy on AI-processed assets affects its compliance boundary.
- In a tight creative budget climate, the $12-24 seat price must still beat free Figma on ROI.
- Meaningful share from high-income Hong Kong/UK markets supports the seat price point.
- Rising acceptance of moodboard-style social collaboration benefits demand for this tool.
- Trust in AI tagging is still forming; manual-review habits haven't fully given way.
- Advancing image-recognition models keep eroding the technical barrier behind AI tagging.
- If Figma or Canva build native asset-tagging, it would erode Kive's standalone position.
- Kive's creative teams runs on cloud generation; 371.7K monthly visits push GPU and transcode energy onto each 'moodboard maker' request.
- If 'moodboard maker' media assets stay on kive.ai, bandwidth and storage accumulate with return visits from United States (29.05%).
- Kive outputs generated media around 'moodboard maker'; training-data and output copyright stay a standing issue in United States.
- Checkout runs on Stripe; platform rules plus likeness or music rights can limit how far 'moodboard maker' may be published.
09 · Five Forces
Porter's Five Forces
Since tagging can call off-the-shelf vision APIs, the barrier to a rival DAM tool is low.
Dependence on underlying vision-model providers means their pricing changes hit costs directly.
Teams can substitute Figma's free collaboration, amplifying buyer bargaining power.
Folder-based cloud storage with manual tagging is a realistic low-cost substitute.
Figma dwarfs Kive (257M vs 371.7K visits); getpoppy.ai is the closer-scaled rival.
10 · 3C
3C Analysis
- Capability: productized dual capability in image auto-tagging and moodboard collaboration.
- Economics: direct Stripe retains higher margin than an MoR, but shifts compliance in-house.
- Structural position: wedged between broad-collaboration giants and similarly scaled getpoppy.ai.
- End users need to search, tag, organize assets, and arrange them into moodboards.
- Pain: hard to search/tag assets. Gain: AI auto-tagging plus unified collaboration.
- Unknown; no LTV, retention, or team-size data given to quantify commercial value.
- Figma is a substitute; teams may use its collaboration tools instead of a dedicated DAM.
- Canva is traffic-adjacent at far greater scale; direct competition is unconfirmed.
- getpoppy.ai has smaller traffic and appears closer in job/budget scope.
11 · STP
STP Marketing Strategy
- Segment first by job: Designers and creative team members doing creative teams, versus evaluators who only search 'moodboard maker' to compare.
- Then cut by who pays for 'moodboard maker' and geography: Design/creative team lead versus free riders, and United States (29.05%) versus the rest.
- Target the layer that can be reached again via Direct and will pay for 'moodboard maker', not every visitor.
- Seats expand the 'moodboard maker' ring, they do not replace the individual job layer; see ICP exclusions.
- AI-tagged DAM: a niche asset-management role in design tooling, not a general canvas.; in the customer's mind it should mean 'moodboard maker', not generic AI.
- The reason to believe 'moodboard maker' is revenue rank #249 and about 371.7K monthly visits, framed against canva.com.
12 · 4P
4P Marketing Mix
- The core bundles an AI-tagged asset library with moodboard collaboration, not a general tool.
- The free tier's limited quota defines how much a team can upload during trial.
- Pro pricing spans roughly $12-24/seat/month, tiered by feature or storage quota.
- The limited free tier front-loads the price gate before any paid conversation.
- Distribution concentrates in Direct (68.5%), with no app-store or partner evidence.
- kive.ai is the only confirmed transaction entry point, with no integration-marketplace evidence.
- The "moodboard maker" keyword and ~10% Organic Search share show real search demand.
- High Direct share implies word-of-mouth-driven growth; SEO remains untapped.
13 · AIDMA
AIDMA Decision Journey
- Attention arrives through Direct (68.51%) and high-relevance entries like 'moodboard maker', not broad brand noise.
- Organic Search at 9.97% is the second attention surface for 'moodboard maker'; kive.ai must make that job obvious to Designers and creative team members.
- Interest comes from translating 'moodboard maker' into a readable creative teams demo, not a feature dump.
- 'dam for creative teams' shows they also want limits, price, or usage detail — the next page has to answer those.
- Desire holds when Kive finishes 'moodboard maker' clearly faster than doing it by hand in one try, and feels closer to that job than canva.com.
- A free or limited trial lowers the cost of wanting 'moodboard maker', otherwise desire dies in the bookmark bar.
- Heavy direct traffic means the brand can be recalled together with 'moodboard maker', or they will search again next time.
- Revenue rank #249 and 371.7K visits become a memory hook only if people also recall 'moodboard maker', not just the brand.
- Action is the first result on kive.ai plus Stripe checkout; an extra signup step drops 'moodboard maker' traffic.
- Let the free quota finish 'moodboard maker' before the upgrade wall to turn interest into payment.
EVIDENCE BOUNDARIESUnknown team/seat counts, preventing total revenue estimation.; Unknown retention/renewal rate, preventing subscription-health assessment.; Unknown funding and team size, preventing assessment of competing with larger platforms.; Unknown whether Canva/Figma integrations exist, affecting channel-strategy judgment.
Sources & Method
Evidence boundaries
Official website: https://kive.ai
Ranking and revenue signals come from Toolify; traffic, channels and country distribution use SimilarWeb methodology; keyword Volume, KD and CPC come from DataForSEO. This is a research snapshot, not investment advice.
Same Category
More in Image / Design
Found your wedge? Ship the site.
Shipsite turns a validated keyword opening like this into a live, SEO-ready site — in days, not months.