Turn better product decisions into better software. Faster.
Teklens does the work between product conversations, Jira and code — across Discover, Define, Build and Operate.
Every use case is connected to Jira and the real code.
Four phases. One context.
Pick a use case to see what Teklens takes on in that phase.
Discover
Understand what matters
Define
Decide what to build
Build
Turn decisions into software
Operate
Keep software healthy
From product conversation to Jira story.
Teklens follows product conversations and turns decisions into executable Jira work – connected to Jira and the real code.
- Conversation
- Decision
- Jira
- Code
Someone asks during refinement: “Teklens, do we already have something like this?” The answer comes from Jira and the code – with a proposal for the next step.
The nine jobs that matter most.
From product conversation to Jira story.
Teklens follows product conversations and turns decisions into executable Jira work – connected to Jira and the real code.
Existing functionality before new development.
Teklens checks every new idea against tickets, earlier decisions and the real codebase before functionality is built a second time.
Controlled access to approved AI models.
Product and engineering work with approved AI models – centrally managed, compliant and secure.
Prioritisation by impact and feasibility.
Features are prioritised by business impact and technical feasibility – grounded in the actual code.
A roadmap anchored in Jira and code.
Connect strategic priorities with Jira, dependencies and actual engineering reality.
Jira and code, continuously aligned.
Teklens continuously compares what is planned in Jira with what is actually happening in the code.
From product decision to development environment.
Open any Teklens artifact directly in your developers' preferred coding environment – with the context already loaded.
Bug triage and resolution without senior capacity.
Teklens triages bugs, finds the likely cause in the code and prepares the resolution – or executes it.
AI spend, visible and budgeted.
Model and token cost per team, project and workflow – with budgets that bite before the invoice arrives.
The full library.
Every use case across Discover, Define, Build and Operate – filterable by phase and audience.
Discover
Gather scattered signals, cluster them and prioritise by value against effort, risk and complexity. Output: a qualified roadmap of prioritised feature candidates.
From product conversation to Jira story.
Teklens sits in product conversations, connects customer and team insights with Jira and real code, and turns decisions into product work.
Customer insights
Clusters scattered customer signals from every source and turns them into prioritised product opportunities.
Existing functionality before new development.
Checks new ideas against tickets, earlier decisions and the real codebase before another feature becomes another project.
Controlled access to approved AI models.
Product and engineering work with approved AI models – centrally managed, with rules for data protection and hosting.
Code-grounded estimation
The first rough triage in Discover: effort, risk and complexity for every incoming idea – estimated against the real code.
Bug statistics
Clusters reported bugs in the backlog and shows where defects pile up – the basis for targeted improvements.
Stakeholder reports & summary widget
Turns bugs, ideas and customer satisfaction into ready-to-send visual reports – on a single prompt.
Domain knowledge from the code
Navigates the codebase semantically and extracts product and domain knowledge – new PMs are productive in days, not months.
Auto-cluster & categorisation
Clusters, categorises and estimates every new idea, bug or ticket automatically on arrival.
Vision-fit check
Finds the stories and epics that carry the vision – and the ones that contradict it.
Define
Work top candidates through in depth against the codebase: code-grounded PRDs, acceptance criteria, edge cases. Output: sprint-ready Jira issues linked to code and requirements.
Prioritisation by impact and feasibility.
Prioritises features by business impact × technical feasibility – grounded in the real code instead of gut feeling.
A roadmap anchored in Jira and code.
Connects strategic priorities with Jira, dependencies and real engineering reality – and flags it when the two drift apart.
Spec → epic with code context
Turns a spec into a build-ready epic with acceptance criteria from real code paths.
PRD expert
Writes code-grounded PRDs that reference real modules, data and constraints.
Acceptance criteria & edge cases
Generates acceptance criteria with edge cases from real code paths the moment a story enters refinement.
Requirement feasibility check
Checks every requirement against the API, schema and test surface of the codebase – before anything is built.
Requirements challenger
Flags weak, ambiguous or contradictory requirements before the build.
Architecture diagrams & blast radius
Renders architecture diagrams from the code and maps the blast radius of planned changes.
API-vs-code drift report
Flags every diagram, PRD and story that has drifted from the code – weekly or on schema changes.
Skill Studio: templates & custom checks
Recurring artefacts and checks as configurable skills – epic criteria, security checks and API-change reviews run the same way every time.
Shift-left compliance & security
Data-protection, compliance, AI-governance and architecture questions surface on the real code in Define – long before implementation.
Build
Estimate grounded in code, map dependencies, allocate into sprints. Quality gates at every status change instead of a sprint-end surprise.
Estimation with risk drivers
The sprint estimate in Build: LOC, complexity and the dependency graph – with the reason behind every number named.
Cross-team dependency graph
Surfaces dependencies from Jira and code at planning time instead of in week two.
Ticket organiser
Moves tickets into sprints and assigns them to epics automatically – roadmap and Jira stay in sync.
Jira and code, continuously aligned.
Continuously compares what is planned in Jira with what is actually happening in the code – and reports the difference.
From product decision to development environment.
Opens any Teklens artifact in the developer's preferred coding environment – branch, context and acceptance criteria already loaded.
Readiness checker
Scores and improves the implementation readiness of tickets before the sprint starts.
Spec conformance check
Checks on every PR whether the code actually implements the story and PRD – drift is caught before the merge.
Release notes generator
Creates structured release notes from many tickets in seconds – a 30-minute review instead of 4–8 hours of writing.
Living docs
Generates living documentation from code and PRDs – support, onboarding and customer docs stay current.
Marketing videos
Creates HTML-based product videos from prompts, scenes and motion profiles – exportable as a standalone player.
Code-aware test strategy
Focuses testing on risky, highly coupled areas – coverage gaps become visible.
Live sprint progress & risk flags
Makes sprint progress and risks visible in real time – daily course corrections instead of waiting for the retro.
Sprint memory
Persistent context per story, epic and PR – analyses, decisions and memories stay in the working context instead of getting lost in individual chats.
Pull request summary
Creates clear summaries of code changes and discussions – for a fast, well-grounded review.
Operate
Support with access to code, logs and past fixes. Prioritise bug vs feature request, protect senior capacity – and feed insights back into Discover.
Incident → commit
Links an incident to the commits and PRs that likely caused it – and the owner responsible.
Bug triage and resolution without senior capacity.
Triages bugs, finds the likely cause in the code and prepares the resolution – or executes it.
Auto-triage & dispatch
Triages and dispatches every new support issue automatically – first-response time drops.
Runbooks & postmortems
Generates runbooks with root-cause analysis – and turns closed incidents into postmortem drafts.
Incident clustering & pattern report
Clusters current incidents into patterns – recurring problems get addressed instead of re-solved.
Closed-loop knowledge
Feeds operational signals – incidents, root causes, edge cases – back into the next discover cycle automatically.
AI spend, visible and budgeted.
Attributes model and token cost to the teams, projects and workflows that cause it – with budgets and limits.
Retro & learnings synthesis
Condenses the team's retro insights on an epic into a retro note – input for improvement and discover.
Fast Lane
The express lane for small changes: short request in, clear goal, working code – no heavy planning phase, still code-grounded.
Give Teklens a real job.
Connect Jira and your code – and let Teklens work on something real.