Choose where to start.
I compare opportunities by impact and feasibility, not by how impressive the demo looks.
ORBIT DISCOVERY SPRINT
AI has potential.Give it direction.
AI consulting, directly with me. Using the O.R.B.I.T. method, we prioritise opportunities, assess risks and define what is worth building for your business.
2–3 week sprint · Clear scope · No development commitment
LOWORBITS / MISSION CONTROLO.R.B.I.T.
PHASE OUTCOME
Clear reading of the starting point.Initial opportunity map and relevant problems.Prioritisation matrix.Shortlist of recommended initiatives.Actionable roadmap and next move decision. Clear reading of the starting point.
HUMAN JUDGMENT / APPLIED AI / OUR OWN METHODFrom uncertainty to a decision ↓
> problem → solution
You have plenty of AI options. Which one is worth pursuing?
Trying tools is easy. Deciding where to invest requires understanding your business. Discovery connects what's holding you back with a sensible next step.
WHAT'S HOLDING YOU BACKO.R.B.I.T. ↗WHAT WE WORK ON IN THE SPRINT
- 01
Everything looks like an opportunity.
Agents, automation, copilots… too many options and no clear priority.
01 / PRIORITISE - 02
The tool arrives before the problem.
Technology is purchased before defining which process or decision needs to improve.
02 / DEFINE Agree on what is worth solving.
I analyse the process, objective and people involved before recommending technology.
- 03
Knowledge is scattered.
Documents, data and experience the team struggles to use together.
03 / ASSESS Understand the foundation.
I review data, knowledge, dependencies and privacy to identify what's ready and what's missing.
- 04
The pilot impresses but doesn't prove value.
Without a metric and an owner, it's hard to decide whether to continue or stop.
04 / SPECIFY Define how to assess value.
Together, we define a use case, a metric and an owner to guide the next step.
> solution
That's Orbit Discovery Sprint.
I work with you to analyse the context, align priorities and turn uncertainty into an action plan. The sprint defines the decision; implementation can follow separately.
A BASIS FOR MAKING DECISIONS
Prioritised opportunities, clear risks and a 30 / 60 / 90-day roadmap. That can also mean not building yet.
View the deliverables> discovery_signals
When an Orbit Discovery Sprint makes sense
This service works especially well when the company feels AI can help, but needs focus before investing.
Choose the situation that feels closest to yours.
Your starting point01 / 06
We want to apply AI but don't know where to start
The management team sees opportunities, but isn't clear on which use case to prioritise.
What this helps you resolve
Opportunity map and first action roadmap.
Your starting point02 / 06
We have too many manual processes
The company detects inefficiencies and repetitive tasks, but doesn't know what to automate first.
What this helps you resolve
Prioritisation of automatable processes by impact, risk and difficulty.
Your starting point03 / 06
We have a lot of scattered internal knowledge
Manuals, documentation, processes and technical knowledge are fragmented.
What this helps you resolve
Viability assessment for AI Knowledge Hub, corporate RAG or private knowledge system.
Your starting point04 / 06
We want to train the team but don't know in what
The company wants to train in AI, but needs to connect training with real roles and cases.
What this helps you resolve
Training proposal by profiles, departments and objectives.
Your starting point05 / 06
We have an AI product or tool idea
There's a clear opportunity, but it's not yet defined as an MVP.
What this helps you resolve
Hypothesis definition, initial scope and next product step.
Your starting point06 / 06
We need to convince management or partners
There's interest, but clarity is missing to justify investment.
What this helps you resolve
Executive document with opportunities, risks, priorities and initial business case.
> orbit_discovery_method
Every phase leaves you with something useful.
A path to understanding your business, prioritising opportunities and deciding the next step. ORBIT Mission Control keeps phases, reports and decisions connected.
What we work on
Observe
We analyse the current context: business, teams, processes, tools, documentation, data and operational friction.
What you take away
Clear reading of the starting point.
01 / O.R.B.I.T.Phase outcome
What we work on
Reveal
We detect AI, automation, corporate knowledge, training or internal tool development opportunities.
What you take away
Initial opportunity map and relevant problems.
02 / O.R.B.I.T.Phase outcome
What we work on
Balance
We evaluate each opportunity by impact, complexity, risk, privacy, data maturity and implementation capacity.
What you take away
Prioritisation matrix.
03 / O.R.B.I.T.Phase outcome
What we work on
Identify
We select the most sensible use cases to advance first and discard those that don't justify immediate investment.
What you take away
Shortlist of recommended initiatives.
04 / O.R.B.I.T.Phase outcome
What we work on
Trajectory
We turn priorities into a 30/60/90 roadmap with next steps, dependencies, resources and possible implementation routes.
What you take away
Actionable roadmap and next move decision.
05 / O.R.B.I.T.Phase outcome
LowOrbits' own platform
The report is not the end of the conversation.
ORBIT Mission Control brings together Discovery progress, deliverables and AI to help you explore the analysis in more depth.
Follow the process
Review the stages, outcomes and next steps of the engagement.
Explore with AI
Ask questions about your reports and revisit the context behind recommendations.
Review how a decision evolves
Organise reports and decisions by version and date. Compare differences and analyse new proposals with AI.
DISCOVERY / Opportunity map
Opportunity map
Decision context
Shared criteria and a data quality review are still missing.
Report exploration
Why isn't this opportunity the first priority?
In this example, it depends on improving data quality first. The initial priority is to prepare that foundation before assessing a pilot.
Context: feasibility assessment and dependencies
DECISION DRIFT
Decisions change. Their context should not get lost.
Decision Drift lets you revisit an earlier version and analyse what changed, what it means and which proposals to review.
Illustrative example · Not a live AI query
Recommendation
Prepare the data before starting the pilot.
Decision context
Shared criteria and a data quality review are still missing.
Recommendation
Assess a focused pilot using the reviewed data.
Decision context
The quality review is documented. The pilot still needs user validation.
My judgment, supported by my own platform.
AI helps explore reports and changes. I work through the recommendations and next step with you.
> who_it_is_for
AI with direction. From your perspective.
Not everyone arrives with the same question. Discovery connects your priority with concrete business decisions.
Explore your profile. One method, different priorities.
01 Business directionFor CEOs
Your priority
You want to understand where AI can generate real impact without depending on trends or vendors pushing their tool.
What the sprint brings you
Strategic clarity and prioritised first moves.
02 Technical judgmentFor CTOs
Your priority
You need to evaluate use cases, architecture, data and risks before each department starts integrating tools on their own.
What the sprint brings you
More controlled technical decisions aligned with business.
03 Product and validationFor founders and startups
Your priority
You want to use AI to operate better or build product, but need to prioritise fast without burning months on poorly focused experiments.
What the sprint brings you
Focus, speed and validation.
04 Operations and knowledgeFor industrial companies
Your priority
You have technical documentation, complex processes and concerns about privacy or industrial property.
What the sprint brings you
Identify safe opportunities for private AI, automation or internal RAG.
05 From idea to decisionFor innovation teams
Your priority
You need to turn ideas and internal pressure to "do something with AI" into concrete, evaluated and defensible initiatives.
What the sprint brings you
Opportunity pipeline and executive roadmap.
> deliverables
What we deliver
Six deliverables to decide where to apply AI, what to prepare and what comes next.
Explore what each deliverable includes.
Where the opportunities areAI Opportunity Map
Opportunity map where AI, automation or knowledge systems can add value. Includes opportunities by area, process, team or function.
What should come firstPrioritized Use Case Matrix
Prioritisation matrix by impact, difficulty, risk, privacy, data maturity and implementation effort.
What you need to prepareRisk & Readiness Assessment
Risk and internal readiness assessment: data, documentation, current tools, dependencies, privacy and adoption capacity.
Your 30 / 60 / 90-day plan30/60/90 Roadmap
90-day action plan divided into clear phases: what to do first, what to prepare, what to validate, what not to touch yet.
The next moveRecommended Next Move
Concrete recommendation for the next step: AI Knowledge Hub, AI Automation, AI App/MVP, AI Training, Private Audio, Intelligence Partner, or don't build yet.
A clear basis for decidingExecutive Decision Brief
Executive document for management with conclusions, priorities, risks, estimated investment and recommended next decision.
> working_protocolO.R.B.I.T. / 05
Strategic discovery yes. Endless consulting, no.
Orbit Discovery Sprint is designed to generate clarity in a few weeks. It doesn't aim to solve the entire AI transformation. It aims to define the first right move.
-
Problem first. Tool second.
We don't recommend tools before understanding process, context and objective.
-
Privacy is considered from the start.
We evaluate privacy risks, sensitive data and intellectual property from the start.
-
Impact matters more than novelty.
Each use case is evaluated by business impact, not by how technically interesting it sounds.
-
A focused scope. A clear next step.
The sprint doesn't try to solve everything. We prioritise decisions. Then execution happens in phases.
-
A use case, a metric and an owner.
If an initiative doesn't have a clear use case, metric or owner, we don't sell it as a priority.
> launch_diagnostic
Start with a controlled diagnostic.
Tell us where you are and what you want to achieve with AI. We'll tell you if it makes sense to start with Discovery.
Frequently asked questions
Select a question to read the answer.
How is it different from an AI audit?
An audit evaluates the current state. Orbit Discovery Sprint goes further: identifies opportunities, prioritises use cases, analyses risks and defines a roadmap. It doesn't stop at diagnosis. It ends in decision.
How long does it take?
Normally between 2 and 3 weeks, depending on the number of areas, interviews, documentation and required depth.
What does the company need to provide?
Access to basic information about processes, tools, internal challenges and priorities. Everything doesn't need to be ordered. Part of the sprint involves understanding that chaos.
Does this sprint include implementation?
Not as the main objective. It defines what to implement first and how. Afterwards it can lead to AI Knowledge Hub, automation, training, MVP or Intelligence Partner.
Does it work for small companies?
Yes, if the company has processes, information or decisions that can improve with AI. You don't need to be a large corporation. You need a real problem and willingness to act.
What if we discover that implementing AI isn't convenient yet?
Then the sprint will already have generated value. Sometimes the best decision is to prepare data, train the team or organise processes. AI isn't always the first step.
What happens after the sprint?
There are normally four routes: launch an AI Knowledge Hub pilot, automate a specific process, train a team, develop an MVP, or start an engagement with Intelligence Partner.
> other_routes
Already know what you need?
You don't always need to start with Discovery. We can begin with a specific need.
Before investing in AI, define your first orbit.
AI can improve processes, decisions, knowledge and productivity. But only if applied in the right place, with the right scope and with risks understood. Orbit Discovery Sprint helps you choose that first move.