create@spiritus.co.zw0777 816 368Harare CBD, Zimbabwe
LLMs · AI workflows

AI & Automation

AI is only useful when it moves a real operational needle: fewer hours on routine work, faster turnaround on ambiguous tasks, better decisions on unstructured data. We build systems that do those things and stay out of the way.

Start a ai & automation projectAll services
Typical engagement · 4 to 12 weeks per use case · iteration retainer

The approach.

We do not retrofit AI into places it does not belong. Before writing any code we map the process, identify where a language model genuinely outperforms a rule, and measure the before-state. If the math does not work, we say so.

Typical engagements include document understanding (invoices, KYC, contracts), customer-facing chat and support agents, internal copilots against company data, and automation pipelines that reduce manual triage. We build on Anthropic, OpenAI, and open-weight models depending on the use case.

Retrieval, guardrails, evaluation, and fallback behaviour are all part of the build. Prompt quality is necessary but not sufficient; what keeps an AI system useful in production is the plumbing around it.

What you end up with.

01

Hours back per week

Automation of the routine manual work that burns staff time and causes burnout.

02

Faster turnaround

Cycle times cut on tasks that were bottlenecked on human review and manual data entry.

03

Safer deployment

Evaluations, guardrails, and human-in-the-loop checkpoints so AI augments rather than replaces judgment.

04

Cost-controlled

Model routing, caching, and usage dashboards so your AI budget is predictable, not a surprise.

What we ship.

  • Process audit and automation opportunity map
  • Custom agent, copilot, or pipeline built for your use case
  • Retrieval system against your documents and data where relevant
  • Evaluation harness, usage logging, and safety guardrails
  • Integration with existing tools including Slack, WhatsApp, email, CRM, ERP
  • Training for staff and an iteration loop on real usage data

Built with.

Anthropic ClaudeOpenAIEmbeddings + pgvectorLangGraph / custom orchestrationn8n / TemporalWhatsApp Cloud API

Typical clients.

01Operations-heavy businesses with repetitive manual processes
02Support teams drowning in first-line tickets
03Finance teams processing invoices and reconciliation manually
04Sales teams needing faster proposal and quote generation

Common questions.

Will my data be used to train models?

No. We use enterprise API tiers where data is not retained for training, and where your use case requires it, we can deploy open-weight models self-hosted.

How do you handle hallucinations?

Retrieval against authoritative sources, structured output contracts, confidence thresholds, and human-in-the-loop checkpoints on anything customer- or money-facing.

Can it run offline?

For many document-understanding and classification tasks, yes. We deploy smaller open-weight models on your infrastructure when connectivity or data residency is a constraint.

What about cost?

We cap spend with model routing (cheap models for easy cases, expensive models for hard ones) and build usage dashboards so you see cost per task in real time.

Related services.

Ready to scope a ai & automation engagement?

Tell us what you’re trying to build. You’ll get a scoped response within 48 hours, no boilerplate.

Start a project