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Services

Focused engagements that remove manual work and make data usable.

Each service below is described in the same way: the problem it addresses, what is typically delivered, the kind of technology involved, and who it tends to suit.

API and SaaS integrations

Business platforms hold overlapping data but do not talk to each other, so information is re-keyed by hand and drifts out of sync.

Typical deliverables

  • Integration design with field-level mapping
  • Authenticated API services with retries and error handling
  • Webhook receivers and scheduled synchronisation
  • Runbook and operational documentation

Example technologies

PythonFastAPIRESTOAuth 2.0Webhooks

Useful for

Teams running several SaaS tools that each hold part of the truth about the same customers, orders, or assets.

Cloud automation and serverless services

Recurring processes depend on someone's laptop, a manual trigger, or a script nobody can see failing.

Typical deliverables

  • Containerised services deployed to Cloud Run
  • Scheduled and event-driven job orchestration
  • Structured logging, health checks, and alerting
  • Secrets and access configuration

Example technologies

Google CloudCloud RunCloud SchedulerPub/SubDocker

Useful for

Organisations that need routine processing to run unattended, predictably, and with visible failures.

Data engineering and PostgreSQL architecture

Data is spread across exports and ad-hoc tables, so there is no dependable record to build reporting or automation on.

Typical deliverables

  • Relational schema design and migrations
  • Ingestion and transformation pipelines
  • Data quality and completeness checks
  • Documented views for downstream consumers

Example technologies

PostgreSQLCloud SQLSQLPythonBigQuery

Useful for

Teams that have outgrown spreadsheets and need a data layer that reporting and automation can rely on.

CRM and workflow automation

Sales and operations processes depend on manual assignment, reminders, and status updates that are easy to skip.

Typical deliverables

  • Process mapping and rule definition
  • CRM configuration, custom apps, and automations
  • Enrichment, scoring, routing, and notifications
  • Reporting on how the rules perform

Example technologies

Zoho CRMZoho CreatorZoho AnalyticsPower PlatformPower Automate

Useful for

Sales, operations, and service teams whose process quality currently depends on individual discipline.

Dashboards and business intelligence

Every team calculates key figures slightly differently, so reporting cycles are spent reconciling numbers instead of using them.

Typical deliverables

  • Agreed KPI definitions and a reporting data model
  • Dashboards with filtering and stakeholder views
  • Scheduled refresh and data freshness indicators
  • Handover so the team can extend the model

Example technologies

BigQueryPostgreSQLSQLZoho AnalyticsPower BI

Useful for

Managers and owners who need consistent operational reporting rather than one-off analysis.

AI-powered internal tools and agents

Skilled people spend hours reading documents, gathering background research, and transcribing information into structured form.

Typical deliverables

  • Defined output schemas and evaluation criteria
  • Document extraction and summarisation workflows
  • Human review and approval checkpoints
  • Source retention and confidence flagging

Example technologies

PythonLLM APIsDocument parsingPostgreSQLCloud Run

Useful for

Teams with high-volume reading, research, or qualification work where accuracy must still be verifiable.

Monitoring and data-collection systems

Data arrives from devices, portals, or partners in inconsistent formats, and gaps are mistaken for genuine changes in performance.

Typical deliverables

  • Source adapters and normalisation into a common model
  • Completeness, plausibility, and reliability checks
  • Threshold-based alerts with actionable context
  • Operational views of asset and data health

Example technologies

PythonCloud RunPostgreSQLTime-series modellingAlerting

Useful for

Operators of distributed assets — including renewable-energy installations — who need trustworthy production data.

Technical discovery and solution design

A problem is understood in outline, but nobody has mapped the systems, data, and constraints well enough to commit to a build.

Typical deliverables

  • Current-state process and systems map
  • Data and integration architecture proposal
  • Risk, security, and access considerations
  • Phased delivery plan with clear scope

Example technologies

Architecture designData modellingIntegration analysis

Useful for

Organisations deciding whether and how to build, before committing budget to implementation.

Not sure which of these fits?

Describe the process as it works today and I'll tell you what I would look at first.

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