01
Product discovery
Define the user, commercial case, and smallest release worth building.
Opportunity mapMVP scope
Flagship service
Build an AI-native SaaS product ready to scale
From product strategy and intelligent workflows to engineering, deployment, and continuous improvement, we turn validated ideas into reliable AI-powered products.
No commitment requiredReply within one business dayConfidential by default
Typical engagement
6–12 weeks
Best for
Founders and product teams
Deliverables
Strategy, UX, product, deployment
Working model
Milestone-based delivery
From friction to forward motion
You bring the challenge.
We build the system behind the solution.
Good delivery starts by understanding what is blocking the business—not by starting with a technology.
What may be happening now
- The opportunity is clear, but the technical roadmap is not.
- AI features feel disconnected from the product experience.
- The MVP works, but its architecture cannot support growth.
- Critical workflows still rely on fragile manual steps.
What the engagement creates
- A validated product and AI workflow strategy.
- An intuitive experience designed around real user decisions.
- A secure, observable backend built for iteration.
- A production release with clear ownership and next steps.
What we build
A complete product capability,
not a disconnected deliverable.
Each capability is tied to a concrete product decision, operating need, or release outcome.
02
AI workflow architecture
Choose where models create measurable value and design fallbacks for when they do not.
Model strategyEvaluation plan
03
SaaS UX and UI
Make complex automated decisions understandable, reviewable, and easy to act on.
PrototypeDesign system
04
Full-stack engineering
Build the application, admin tools, APIs, and data flows as one maintainable product.
Web appAdmin workspace
05
Identity and billing
Set up secure access, account roles, subscriptions, and the operating controls a SaaS needs.
AuthenticationBilling flows
06
Deployment and iteration
Launch with monitoring and a delivery system that supports learning after release.
CI/CDObservability
How delivery works
Seven phases.
One visible path to launch.
Every phase produces something reviewable. Select a step to see the work, output, timing, and your role.
Relevant work
Proof in the product,
not a wall of logos.
A closer look at a related challenge, what we delivered, and the operational outcome.
AI-assisted SaaS · E-commerce operations
FeedIQO
- Client challenge
- Shopify teams and agencies needed a dependable way to spot Merchant Center issues before they affected advertising performance.
- Solution delivered
- We built a focused monitoring product that centralizes feed problems, suspension risks, evidence, and reporting in one operational workspace.
- Outcome
- More than 500 stores monitored, with the client reporting roughly 40% faster issue resolution.
Next.jsTypeScriptPostgreSQLGoogle APIs
Open projectMore relevant projects
Different contexts. The same delivery discipline.
AI learning platform · Medical education
Med Academy DZ
A single learning environment now supports more than 10,000 active users and gives the team a foundation for new study formats.
Product designWeb platformAI integration
View project
SaaS platform · Fitness
FitFlow
More than 250 coaches have been onboarded, with repeatable plan delivery replacing a fragmented manual workflow.
SaaS product designFull-stack buildAutomation
View project
Marketplace · Health and fitness
BodyVibe
The product connects a multi-sided service journey in one experience and has supported more than 5,000 consultations.
Marketplace UXWeb engineeringAI integration
View projectEngineering approach
The stack follows the product.
Not the trend cycle.
We select technology around product requirements, scalability, maintainability, team capability, and long-term ownership.
Product layer
Next.js · React · TypeScript
Fast, accessible interfaces with a maintainable component and type system.
Intelligence layer
Model APIs · Retrieval · Evaluations
The model and retrieval approach follows the workflow, accuracy needs, and ownership constraints.
Data and backend
Node.js · Python · PostgreSQL
Clear service boundaries and durable data models support iteration without rewrites.
Production
Cloud infrastructure · CI/CD · Monitoring
Automated releases, logs, metrics, and recovery paths make the product operable.
Modular architecture
Secure authentication
API-first boundaries
Automated checks
Why Perceptrondev
A product partner built
around clear ownership.
The team stays close to the problem, makes decisions visible, and leaves you with a product you can operate.
Strategy and engineering together
Product decisions are tested against user value, delivery risk, and long-term ownership from the start.
Direct access to builders
You collaborate with the people designing the flows and making the technical decisions.
Visible delivery
Shared milestones, written updates, and working demonstrations keep progress and trade-offs clear.
Production-ready handover
Testing, deployment, monitoring, documentation, and ownership are part of delivery—not afterthoughts.
Business-led technical choices
Technology is selected around the product, constraints, team, and total cost of ownership.
Support that can evolve
Move from launch stabilization to ongoing improvement or a dedicated team as the roadmap grows.
50+
Projects delivered
30+
Happy clients
4.9/5
Client rating
98%
On-time delivery
Client feedback
What working together
looks like in practice.
Feedback connected to shipped work and a named client—not an anonymous marketing claim.
AI-assisted SaaS
AC
Adam Cohen
Founder · FeedIQO
“PerceptronDev turned a rough spec into a tool our agency uses every day. Catching Merchant Center issues before they kill ad spend used to be guesswork — now it’s a dashboard. Resolution time dropped about 40%.”
1 / 1
Ways to work together
Choose the engagement
that matches the uncertainty.
Start with a focused decision or assemble the full team. Scope and cadence stay explicit in either model.
011–2 weeks
Focused product sprint
- Best for
- Validating a high-value workflow or shaping an existing idea.
- Includes
- Discovery, prototype, technical direction, and delivery roadmap.
026–12 weeks
Complete product build
- Best for
- Taking a defined product from scope through production launch.
- Includes
- Product design, engineering, QA, deployment, and handover.
033+ months
Dedicated product team
- Best for
- A roadmap that needs consistent design and engineering capacity.
- Includes
- A stable cross-functional team, sprint planning, and reporting.
04Monthly
Improvement and support
- Best for
- Scaling, modernizing, or operating a product after launch.
- Includes
- Prioritized enhancements, maintenance, monitoring, and support.
Questions, answered
Clarity before
commitment.
The practical questions teams ask before beginning a ai-native saas engagement.
A useful first conversation
Have a product idea?
Let’s make the next step clear.
Tell us what you are building, where you are blocked, and what success looks like. We will review it and recommend the most effective next move.
No commitment requiredResponse within one business dayYour information remains confidential
Project brief
A few details.
A practical reply.
The form takes about three minutes. Your selected service is already attached, and your entries stay in place if anything needs correcting.
Service-specific review
No sales-script handoff
Clear recommendation on the next step
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