Every generated screen needs a second pass
Off-brand spacing, wrong type scale, colors that never existed in your system.
adlenticaSoftware doesn't guess, Adlentica does not either.
Every output is driven by context, intent, and cognitive brand intelligence — from the first prompt to the shipped interface.
- Context-aware generation, not guesswork
- Every artifact traced to intent
- Ships with your design system built in
Output 0417 / verified
Rendered from intent in 1.8 seconds.
adlentica.comthink. design. adlentica
The promise
Software that arrives finished.
- 01
Ship interfaces that already match your brand on the first pass.
- 02
Cut review cycles from three to one without losing rigour.
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Keep every decision traceable back to the intent behind it.
Pain points
Generation is cheap. Correction is not.
Context dies between prompts
You re-explain the same data model and the same tone rules, session after session.
Reviews argue about diffs
Nobody can tell which decision produced which line, so everyone relitigates everything.
Velocity looks fast, shipping stays slow
Output volume goes up while the amount that survives review stays flat.
The three pillars
A context engine, not another chat box.
Adlentica binds reasoning, memory, and provenance into a single substrate. Everything you ship on top of it inherits all three.
01 · Reasoning
Grounded reasoning
Every prompt routes through your data before it routes through the model. Retrieval, tools, and verification are first-class citizens, not afterthoughts.
- Structured planning with tool-graph execution
- Automatic citations for every claim
- Self-critique before responding
02 · Memory
Persistent memory
A living store of what your team cares about, what you rejected, and how you work. Direction compounds across sessions instead of resetting.
- Hierarchical episodic and semantic layers
- Automatic decay, refresh, and consolidation
- Portable per-project memory vectors
03 · Provenance
Traceable outputs
Every artifact carries a trail: which source, which step, which decision. Audit-ready for enterprise, useful for everyone else.
- Reasoning trace exposed in every response
- Deterministic replay of any generation
- Row-level lineage for regulated teams
The process
Four steps from intent to shipped.
- 01
Ingest
Adlentica reads your repository, design tokens, and brand rules — not just the prompt in front of it.
- 02
Resolve
Intent is checked against real constraints. Conflicts surface before generation, not after review.
- 03
Generate
Output ships inside your system: your spacing, your type scale, your tone, your data model.
- 04
Compound
Every accepted and rejected decision feeds brand memory, so the next pass starts further ahead.
Product BTS
Built from the inside out.
Adlentica isn't a wrapper around a model. It's a stack of specialized systems that turn raw intent into shippable, on-brand software.
Context engine
Ingests your repo, design tokens, and brand rules so every prompt is resolved against real constraints, not imagination.
Constraint resolver
Cross-checks intent against your data model, tone, and prior decisions. Conflicts surface before generation, not after review.
Brand memory layer
Stores every accepted and rejected decision as persistent signal. The next session starts where the last one left off.
Output forge
Generates interfaces, copy, and logic inside your own system — your spacing, your type scale, your conventions.
Traceability graph
Each artifact carries a lineage back to the intent, decision, and constraint that produced it. Reviews argue about rationale, not diffs.
Feedback loop
Every shipped or rejected output closes the loop. The model learns what your team actually accepts, not just what it generates.
Testimonials
Trusted by teams that ship deliberately.
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“Adlentica reads the intent behind our backlog. What used to take three review cycles now ships in one.”
Elena Voss
Head of Product, Tandem
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“The first tool that actually preserves our design system instead of fighting it.”
Marcus Chen
Design Lead, Northwind
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“It feels like the interface remembers every decision we made and builds forward from there.”
Sara O'Brien
Engineering Director, Quarry
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“We stopped arguing about diffs and started arguing about direction. That's the shift.”
Daniel Ríos
CTO, Fable Studio
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“Context-aware generation sounds like a tagline until you see it keep your brand voice intact.”
Priya Nair
Brand Director, Lithos
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“The output carries lineage back to the original intent. Audits became trivial.”
James Holden
VP Engineering, Meridian
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“Adlentica reads the intent behind our backlog. What used to take three review cycles now ships in one.”
Elena Voss
Head of Product, Tandem
+
+
“The first tool that actually preserves our design system instead of fighting it.”
Marcus Chen
Design Lead, Northwind
+
+
“It feels like the interface remembers every decision we made and builds forward from there.”
Sara O'Brien
Engineering Director, Quarry
+
+
“We stopped arguing about diffs and started arguing about direction. That's the shift.”
Daniel Ríos
CTO, Fable Studio
+
+
“Context-aware generation sounds like a tagline until you see it keep your brand voice intact.”
Priya Nair
Brand Director, Lithos
+
+
“The output carries lineage back to the original intent. Audits became trivial.”
James Holden
VP Engineering, Meridian
+
+
“Adlentica reads the intent behind our backlog. What used to take three review cycles now ships in one.”
Elena Voss
Head of Product, Tandem
+
+
“The first tool that actually preserves our design system instead of fighting it.”
Marcus Chen
Design Lead, Northwind
+
+
“It feels like the interface remembers every decision we made and builds forward from there.”
Sara O'Brien
Engineering Director, Quarry
+
+
“We stopped arguing about diffs and started arguing about direction. That's the shift.”
Daniel Ríos
CTO, Fable Studio
+
+
“Context-aware generation sounds like a tagline until you see it keep your brand voice intact.”
Priya Nair
Brand Director, Lithos
+
+
“The output carries lineage back to the original intent. Audits became trivial.”
James Holden
VP Engineering, Meridian
12 teams onboarded94% kept as-is
Project spotlight
How a team shipped 2.1x faster with context.
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Meridian Design Co.
A product agency rebuilding a client dashboard across multiple brands. Before Adlentica, every screen needed 3–4 review passes. After onboarding their design tokens, tone rules, and data models, generated screens started matching brand on the first pass.
- Team12-person product squad
- Context source3 design systems, 2 APIs
- Timeline6 weeks to first ship
Pricing
One rejected pass costs more than a month.
$29/ month
For one operator shipping their own product.
- +1 workspace
- +Context engine
- +Design system sync
- +Community support
$89/ month
For teams that review each other's work.
- +5 seats included
- +Brand memory across sessions
- +Traceable output lineage
- +Priority support
Custom
For orgs with many products and one system.
- +Unlimited seats
- +Self-hosted context
- +Audit exports
- +Dedicated engineer
Risk reversal
The risk sits on our side.
You've been burned by tools that promised context and delivered autocomplete. Try Adlentica on a real project — if it doesn't hold up, walk away whole.
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30-day full refund
If Adlentica doesn't reduce your review cycles, you get every cent back. No forms, no call.
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Keep what you generated
Everything produced during your trial stays yours, refund or not. It's your code and your brand.
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Cancel in one click
No annual lock-in, no offboarding fee. Export your context and brand memory whenever you want.
Get started
Bring your context. Keep your taste.
Point Adlentica at your repository and brand rules. It reads the intent behind what you already built, then generates forward from there.
1.8sIntent to interface
94%Output kept as-is
0Design system drift