Dashboard – initiatives at a glance
01 · Discover
Discover
Signals from every source are clustered and prioritised against vision, personas and code. You see value vs effort instead of gut feel.
The Product
Context Engine
Teklens is Software product management × code intelligence. Its heart is the Context Engine: it reads your real code, your tickets and your decisions – and connects everything into a graph that every answer, spec and estimate uses. Teklens has read your code. Generic tools guess.
Why it's special
Other AI tools see scraps – a Slack thread here, a Confluence page there. The Context Engine turns them into a living graph of code, requirements, decisions and people. Every idea is linked to the components it touches, every ticket to the real code path, every estimate to what's actually in the repository. The context stays – sprint after sprint, person after person.
Graph, not copy-paste
Knowledge is modelled once and reused everywhere – not pasted into every prompt by hand.
Priorities with a reason
Scattered ideas, bugs and feedback become a continuously prioritised roadmap – every position backed by value against effort, risk and complexity, grounded in the real code.
Master playbook
You decide what's canonical. Teklens keeps the state per initiative current and makes decisions traceable.
Private AI, model-agnostic
Pick the model per project (Claude, GPT, Gemini). CH/EU hosting, no training on your data.
One context layer over everything
Integrated, always in sync.
Every source feeds a single Context Engine. The answer shows up where you work – no tab-hopping.
01 – Context
Code
Every repo, semantically indexed
Jira
Issues & sprints
Confluence
Docs & decisions
Git history
Features & experts
02 – Context Engine
Context Engine
Every query goes through the Context Engine. It assembles the relevant context from every source.
Semantic searchFinds code and docs by meaning, not by keyword.Knowledge GraphConnects tickets, PRDs, commits and owners as a network.LSP traversalFollows symbols and call graphs through the codebase.Cross-repoSpans multiple repos – one shared context.
03 – In your tools
Embedded in Jira
Answer right inside the ticket – PROJ-2481
Teklens web app
app.teklens.ai – same context, own workspace
Always in sync – same context in Jira and on the web.
Built along the cycle
Discover · Define · Build · Operate – the Context Engine works in every phase against the same graph.
Risk analysis – edge cases surfaced
02 · Define
Define
The Impact & Feasibility Matrix prioritises by value, effort and risk. Code-grounded PRDs, acceptance criteria and risk analyses from real code paths – estimates are backed by the repository.
Live view – progress in real time
03 · Build
Build
A live agent team per initiative – PM, PO, engineering – works in the same context, across live conversations and artefacts.
Support – PRD & evidence
04 · Operate
Operate
Support, incidents and root causes flow back into the graph – and into the next Discover round.
Why not Rovo, coding agents or your own RAG?
All three are legitimate paths – and all three leave the same piece on the table. Compared honestly:
Jira Rovo
Stays inside Atlassian. Sees tickets and Confluence pages, but doesn't know your code. Answers stay at the ticket layer.
Coding agents
They speed up execution – that's what they're great at. But they leave everything before and after untouched: overview, prioritisation, clean inputs. Automating bad input just ships the mess faster.
Build your own RAG
Full control – and a second product you build and maintain. The living graph across code, tickets and decisions is exactly the piece that gets most expensive to build in-house.
Teklens
Connects tickets, decisions and your real code in a single graph. Code Intelligence anchors every idea to the components it touches – across all tools. Coding agents get clean input, and Jira stays the leading system.
Hold every solution against this list.
Eight selection criteria – whether the answer ends up being Teklens or not.
- Does it read our real code and link it to ideas, tickets and incidents?
- Does context persist per initiative and grow – without us maintaining it?
- Does it prioritise value against effort, risk and complexity – with a traceable reason?
- Do acceptance criteria and edge cases come from real code paths, before the build?
- Do we see live where every initiative stands – checked at every status change?
- Do learnings from support and operations flow back into planning?
- Does it connect to Jira, Confluence and GitHub instead of replacing them?
- Data and hosting CH/EU, no training on our data, model choice per project?
What the Context Engine actually does
Five building blocks that sit on top of the Context Engine.
Spec → Ticket
Product writes the spec. Teklens translates it for engineering with code context, creates the Jira ticket and drafts the QA plan.
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Standup automation
Teklens summarises overnight activity, flags blockers and writes the standup – ready before your first meeting.
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Role handovers
Every handover carries the context, acceptance criteria and an audit trail. No more "that wasn't in the spec".
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Sprint memory
Architecture decisions, stakeholder discussions and past sprint history – persisted per team and per role.
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Portfolio cockpit
Alignment scores, critical risks and stealth projects – flagged proactively, before they escalate in the steering meeting.
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See the Context Engine on your own code.
30-minute live demo on your repo. No sales.
A founder replies directly.