From stakeholder requirement
to implementation-ready work in minutes.
Speqtor is an enterprise layer between business intent and AI-driven implementation. It reads a company's own repositories and turns a requirement into implementation-ready epics, stories and AI-ready prompts — today. Full code generation with developer review is where the roadmap leads.
See Speqtor turn a requirement into implementation-ready work
A short walkthrough of the product in action, from a stakeholder requirement to AI-ready prompts.
The path from requirement to code is long, manual, and lossy
A single business requirement passes through many handovers before a developer writes the first line. Each handover takes time, and each one is a place where intent gets diluted.
Business intent becomes implementation-ready work
Speqtor continuously analyzes a company's repositories and maintains an up-to-date understanding of its architecture, dependencies, business logic and integrations. Today, a requirement goes straight to implementation-ready epics, stories and AI-ready prompts. The next step on the roadmap: generated, review-ready code.
Analyze once
The repository is analyzed upfront, once, rather than re-explained to a model for every new task.
Reuse context
Speqtor builds a persistent, structured understanding of the system that stays current as the codebase changes.
Send only what matters
For each new requirement, only the relevant slice of that understanding is sent to the model — turning a process that used to take months into one that takes minutes.
Speqtor is top-down. Copilot and Cursor are bottom-up.
Copilot helps a developer write code that's already been scoped. Speqtor helps the organization decide what should change, where, and how — before a developer opens the file.
- Bottom-up, built for developers
- Start from code that's already scoped
- Help implement known, well-defined tasks
- Depend on the user supplying the right context
- Top-down, starts from business intent
- Understands repositories, architecture and dependencies on its own
- Translates intent into implementation-ready work
- Produces AI-ready prompts today — full code generation is the roadmap
Five use cases, before and after Speqtor
Drawn directly from proof-of-concept work with early pilot partners.
A BA/PO receives a requirement, and developers spend time locating the right repositories, services, business logic and dependencies.
The requirement is translated directly into implementation-ready epics and stories, plus AI-ready prompts a developer can run in their coding tool of choice.
Long refinement cycles compress into minutes — and set the stage for full code generation.
A small business change can touch several services, APIs and teams. Dependencies are easy to miss and require multiple clarification meetings.
Speqtor identifies affected repositories, APIs, integrations, dependencies and risks before implementation begins.
Fewer meetings and lower implementation risk.
AI coding tools repeatedly need large repository context and manual prompting to understand what should change.
Speqtor reuses its structured system understanding and sends only the relevant context to the model.
More precise AI output, at a fraction of the token usage.
Documentation is written by hand, drifts out of date the moment code changes, and rarely reflects how systems actually connect.
Because Speqtor already holds the complete, structured context of the system, documentation is generated straight from reality — and stays current as the code evolves.
Documentation becomes dramatically easier — always accurate, with far less manual effort.
A non-technical PM has zero touch points with the code or how systems really work. Every feasibility and scoping question has to route through engineers.
Speqtor gives PMs friction-free access to the system's real structure, dependencies and constraints — so they can scope features and explore what's actually possible on their own.
PMs plan better features and possibilities that simply weren't visible before.
Built to sit inside an existing stack, not replace it
Easy to integrate, and designed around enterprise security requirements from day one.
Implementation & integration
- Connects to existing repositories with read-only access
- Works alongside the customer's existing development workflow
- Integrates with existing AI providers using the customer's own API credentials
- No need to replace existing developer tools or infrastructure
Security & data handling
- Source repositories are processed only for analysis and deleted immediately after
- Persistent Speqtor data is stored in Sweden
- All stored data is encrypted at rest
- No persistent copy of the source repository is retained
- Only structured, purpose-specific system information is kept
- AI-generated changes stay human-in-the-loop, reviewed before merge
Strong pilot interest from software-intensive companies
Momentum has built through direct conversations with engineering and product leaders at companies that feel this handover cost every day.
Early demand points to a clear pattern: organizations that ship software at scale are actively looking to compress the distance between a business requirement and a developer's first commit — and are willing to pilot new tooling to get there.
Built by people who've felt this handover firsthand
A small, focused team covering product and go-to-market.
I have a track record of making things happen.
Out of 2,000 applicants, I was one of 10 selected to become a firefighter. While working full-time, I earned an engineering degree from KTH. I later went from barely being able to swim to qualifying as a rescue diver.
Throughout my career, I’ve consistently looked for ways to improve how things are done — from emergency services to software development.
I’ve had 100 ideas. 90 were too late. 9 were bad. Speqtor is the one I’m going all the way with.
I’m a Staff Software Engineer specializing in AI, code intelligence and large-scale analytics. I’ve built data-intensive systems across fintech and enterprise revenue technology, with deep experience turning complex, high-stakes data into scalable software products.
I’m a senior developer who’s just as at home in a codebase as I am in a room full of people — and that mix is my edge. I understand exactly what Speqtor does under the hood and can translate it into what it really means for a business. I build genuine trust with engineering and product leaders and turn early interest into lasting partnerships.
Test Speqtor for yourself
Want to go hands-on? Visit our application and log in to get started — you can run a real requirement through Speqtor and see the output first-hand.
- 01 Visit the application
- 02 Log in
- 03 Run a real requirement
Log in with your credentials to access the application.
Building the layer between intent and implementation.
We're happy to share the full data room, product walkthrough and pilot results with interested investors.