Where we start

The technology is rarely the best place to start.

A process may be slow because information is missing. A report may be ignored because nobody owns the decision. An AI tool may fail because the business rules were never agreed. We begin underneath the technology: the problem, the process, the information, the ownership and the way success will be measured.

What we hear most often

  • “There is too much manual inputting.”
  • “We have several systems that do not talk to one another.”
  • “Everything goes through one person.”
  • “We have reports, but nobody does anything with them.”
  • “We know AI is coming, but we do not know where to start.”
  • “People use AI, but they are not confident they are using it well.”

None of those start out as AI problems. They are questions about work, information and ownership — and that is where a useful answer starts too.

Abstract brand graphic PNG or SVG · 600 × 450

Something from the Baltic identity. Not a robot, brain or humanoid figure.

We will tell you when AI is not the answer.

Sometimes the fastest improvement is a better process, trusted data or proper use of a system you already pay for.

No obligation

Your first conversation

  • What you are trying to improve
  • Where time or quality is being lost
  • Who experiences the problem day to day
  • An honest view on whether we can help
Start the conversation

The five questions underneath every engagement

01
Problem

What are we actually trying to improve?

02
Process

How does the work really happen, including exceptions and workarounds?

03
Information

Is the data and context good enough for this particular purpose?

04
Ownership

Who remains responsible when the technology gets it wrong?

05
Measurement

How will we know the work is actually better?

The model

Consult. Build. Sustain.

01

Find what is worth doing

Consult

We sit with the people doing the work, map how it really happens, review the systems and information underneath it, and prioritise the opportunities by value, effort and risk.

Explore Consult

02

Make the improvement real

Build

We design and deliver practical data, systems, automation and AI work. That may be a connected workflow, a reporting product, an internal assistant or a better way to use the platform you already own.

Explore Build

03

Keep improving without us

Sustain

We document, hand over and support what we build. Where there is a genuine skills need, Baltic's training and apprenticeship capability can help your people learn on the real systems and problems inside your organisation.

Explore Sustain
01 Problem
02 Process
03 Information
04 Automation
05 AI
06 Handover

Start small enough to finish. Use what you already own before adding a platform. Never call a prototype a supported service.

Groundwork · the front door

Get the room excited about what is possible — and grounded in what is useful.

Groundwork is an interactive workshop for leaders and managers who want to understand what AI and automation could mean for their organisation without being pushed towards a fashionable solution. It combines practical examples, honest discussion of risk and structured activities that help the room identify where work could genuinely improve.

  • A shared language across leaders and teams
  • An honest view of what is genuinely possible now
  • A way to put a cost on repeated administration
  • Where the machine should stop, and why
  • One or two practical next steps you own

What we can help with

Capability families, not a catalogue

Which of these you need depends on the problem, not on what we would prefer to sell. Most engagements draw on two or three.

Problem first · Measured · Built to hand over ·
Automation

Workflow and process automation

Approvals, reminders and routing. Repeated document and email workflows. Data moved between systems by something other than a person.

CRM

Connected customer workflows

CRM configuration and workflow improvement, follow-up and pipeline alerts, call information into the CRM, and data-completeness checks that hold.

Data

Reporting and decision support

Metric and definition design, dashboards and reporting packs, scheduled pipelines, threshold alerts and commentary someone will actually act on.

AI

AI and unstructured information

Calls, documents, emails and feedback summarised, classified and searched at a scale nobody could manage by hand — with human review where it matters.

Microsoft 365 & integration

The systems you already own

Power Automate, SharePoint, Outlook, Teams and Excel processes. API integrations, webhook handlers, scheduled services and small internal tools built around one clear business problem.

Why us

Built from lived experience, not a transformation playbook

We are an SME too

  • A North East SME modernising its own operation
  • Limited capacity and legacy systems are familiar ground
  • We know value has to be proved before it scales

We have done the internal work

  • Data, reporting, CRM, automation and AI in a live organisation
  • Including the assumptions that turned out to be wrong
  • And the adoption problems that arrive after launch

We build as well as advise

  • A roadmap is only useful if it leads somewhere
  • Discovery can move into a controlled build
  • Where the case is genuinely clear, and not before

Capability, not dependency

  • 17+ years developing people through apprenticeships
  • Handover and development are part of the model
  • Not an afterthought once the invoice is paid
We are willing to say no. Sometimes AI is the wrong tool, and sometimes the fastest improvement is a better process, trusted data or proper use of a system you already pay for.

Proof

The work we have done on ourselves

We are new as a consultancy, and we are not going to borrow somebody else's case study. What we do have is several years of doing this inside a live organisation, with the assumptions written down so you can judge them yourself.

The figures below are modelled from internal data. They describe capacity released rather than audited cash savings, and we are happy to show the workings.

Our story
Automation & AI

Sales preparation that used to be done by hand

Finding a suitable local candidate, checking travel distance, reading a CV, pulling out the relevant points and writing them into a customer email. We connected candidate data, a public postcode source, AI-assisted CV analysis, Salesforce and Salesloft so that most of the preparation now happens automatically.

  • ~6 minper task, before
  • ~£128kmodelled annual capacity released
  • ~2xthe reply rate of other steps

Modelled from internal volumes and salary assumptions. Not an audited cash saving.

Automation

Scheduling that only needs doing once

Coaches used to create training events, emails and individual calendar invitations by hand for every cohort. A connected workflow now takes the dates the coach enters once and handles the downstream administration from there.

  • ~1,440 hrsof annual admin modelled
  • ~£36kmodelled annual time value
  • ~16 hrsof combined effort to build

Based on eight hours per cohort, across roughly 60 coaches and three cohorts a year.

Data & reporting

A reporting capability built from scratch

Retention analysis, early-risk measures, salary analysis, employer segmentation, caseload management and learner-risk reporting, built so the business could see where intervention was needed rather than guess.

  • Mid-60s → high-70slearner retention across the period

Data was one contributor among several. We do not claim it caused the improvement on its own — a dashboard changes nothing without a process behind it.

Data quality

Prospecting data worth trusting

We redesigned parts of our prospecting data and workflow across ZoomInfo, Salesforce, Salesloft and Tableau. The clearest measured outcome was email deliverability.

  • 20% → 5.8%email bounce rate

The wider change also met adoption and operating-model problems, and was paused. That lesson shaped how we handle handover now.

Straight talking

Automation or AI? They answer different questions.

We do both. The best solution is the least complex system that reliably produces the outcome you need — and more often than people expect, that is rules rather than a model.

Often the answer

Automation, when

  • A person is the integration layer between two systems
  • The same email, document or quote goes out again and again
  • An approval runs on somebody remembering to chase
  • A report gets rebuilt by hand every week
  • The rules can be written down and agreed

Cheaper, quicker and identical every time. A great deal of lost capacity lives here.

Worth it when it fits

AI, when

  • The work means reading things: transcripts, emails, documents
  • Somebody summarises or spots patterns by hand today
  • It helps a person decide, rather than deciding for them
  • You hold information you never get round to using
  • Words need writing: summaries, commentary, first drafts

Genuinely powerful on the right job. An expensive way to do what a rule could have done on the wrong one.

Capability is not consent. What a system can do, and what your people should willingly hand over, are two different questions.

Who we work with

Real operational volume, not much spare capacity

Usually somewhere between ten and a few hundred people. Enough volume that manual work and poor information carry a genuine cost, and not enough slack to go and investigate it properly.

  • Fragmented systems, spreadsheets and email-based processes
  • Repeated rekeying between tools that will not talk to each other
  • Leaders interested in AI but unsure where it genuinely fits
  • One or two self-taught experts who have become a key-person risk
  • Reports that exist, but that nobody acts on
  • A need to improve without commissioning a transformation programme

Before you ask

The questions we get first

No sales waffle. If we are not the right fit, we will say so in the first conversation.

All questions

AI is one of the tools we use, not the answer we start with. We work across process, data, systems, automation and AI. The right intervention depends on the problem.

We ask what the organisation is trying to improve, where time or quality is being lost, who experiences the problem and what systems or information are involved. If we are not the right fit, we will say so.

No. Understanding the condition, meaning and ownership of your information may be part of the work. We will be honest if the data foundations need attention before a build makes sense.

Where the opportunity is clear, measurable and within our capability, yes. We use a staged model, so a diagnostic does not automatically commit either side to a large build.

No. The consultancy work stands on its own. If it reveals a genuine long-term skills need, we can explore whether a Baltic development pathway is relevant — but that is a separate conversation, and entirely optional.

Tell us what is getting in the way.

You do not need a finished brief or a preferred technology. Tell us what is slow, repeated, difficult to trust or harder than it should be. We will arrange a short conversation and tell you whether we think there is a useful next step.

  • A conversation, not a pitch
  • We will say if we are not the right fit
  • No obligation to buy a build