TEJVON

Solutions

ENGINEERING SOLUTIONS
FOR COMPLEX
PRODUCT CHALLENGES

Most visitors don't search for services — they search for answers to specific product engineering challenges. Identify yours below.

Solution Area 01

Building Connected Products

Wearables · Consumer Electronics · Healthcare Devices · Smart Products

Common challenges

  • Device onboarding fails in real-world conditions
  • BLE connections drop under normal usage
  • OTA updates fail silently or leave devices bricked
  • Synchronization between device and cloud is unreliable

Business impact if unsolved

  • High support volume from connection failures
  • Poor user retention in the first 7 days
  • Product reviews dominated by connectivity complaints
  • Engineering time consumed by reactive firefighting

Recommended approach

Architecture Review → Connectivity Strategy → Device Lifecycle Design → Reliability Engineering

Solution Area 02

Launching an MVP

Founders · Early-Stage Startups · New Product Initiatives

Common challenges

  • No clear technical roadmap from idea to launch
  • Uncertainty about which architecture to choose
  • Budget and timeline constraints with no engineering partner
  • Risk of making wrong foundational decisions in sprint one

Business impact if unsolved

  • Delayed launch while competitors move faster
  • Expensive architectural rewrites in month four
  • Technical debt that blocks every feature after launch
  • Investor conversations stalled by technical uncertainty

Recommended approach

Discovery Sprint → Product Roadmap → MVP Architecture → Technical Planning

Solution Area 03

Improving BLE Reliability

Connected-Device Teams · IoT Companies · Hardware Startups

Common challenges

  • Connection drops after 10–15 minutes of use
  • MTU negotiation failures on specific Android versions
  • Pairing reliability varies wildly across device OEMs
  • Battery drain from inefficient BLE scanning strategies

Business impact if unsolved

  • Poor app store ratings citing connectivity
  • Support team overwhelmed by reproducible bugs
  • Product abandonment before users see the core value
  • Engineering velocity killed by regression testing

Recommended approach

Connectivity Audit → Protocol Optimization → Reliability Testing → Lifecycle Design

Solution Area 04

Scaling Mobile Platforms

Growth-Stage Companies · Product Teams · Engineering Leaders

Common challenges

  • Feature delivery slowing down as codebase grows
  • Architecture bottlenecks block multiple team members
  • Legacy XML codebase making Compose adoption impossible
  • Performance regression in every new release

Business impact if unsolved

  • Missed product roadmap milestones
  • Increasing technical debt with each sprint
  • Developer frustration causing team attrition
  • Product instability reducing user trust

Recommended approach

Architecture Review → Modular Refactor → Compose Migration → Performance Profiling

Solution Area 05

AI-Powered Experiences

SaaS Companies · Product Teams · Digital Platform Builders

Common challenges

  • Manual workflows consuming user time and attention
  • Knowledge fragmented across apps and data sources
  • AI feature ideas with no clear implementation path
  • Voice interactions feeling unnatural and unreliable

Business impact if unsolved

  • Operational inefficiency reducing user engagement
  • Competitors shipping AI features faster
  • Low user retention from poor productivity value

Recommended approach

AI Feature Discovery → Architecture Design → LLM Integration → Voice System Implementation

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