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Tech by SLS

> Deep-tech engineering · Cloud-native · Enterprise AI

Learn it. Build it. Ship it.

Senior engineering for systems that cannot afford to be wrong: automotive map data, low-latency distributed backends and production AI. Architecture you can defend, code you can run.

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// core pillars

Four tracks, one standard of engineering.

Pick one or combine them. Each track has defined deliverables and a clear way to work together.

  • 01

    Deep-Tech Software Engineering

    Automotive-grade software: NDS and ADAS map data pipelines, geospatial processing and low-latency distributed systems where milliseconds and correctness both matter.

    • C++
    • Rust
    • Go
    • NDS / ADAS
    • Geospatial
    Deliverables and approach
  • 02

    Cloud-Native & Backend Architecture

    Backends that stay boring in production: event-driven pipelines, clear service boundaries and data stores chosen for the workload, not the trend.

    • Go
    • Rust
    • Python
    • PostgreSQL
    • Redis
    Deliverables and approach
  • 03

    Enterprise AI & Agentic RAG Systems

    Production LLM pipelines with evaluation, guardrails and cost control. Retrieval that is measured, agents that are bounded, internal tools that people actually use.

    • Python
    • Claude / OpenAI APIs
    • pgvector / Qdrant
    • LangGraph
    • Evals
    Deliverables and approach
  • 04

    Technical Product Architecture & Advisory

    Senior technical judgment on demand: build-vs-buy, architecture decisions, vendor and hiring assessments, and a roadmap your engineers and executives both believe.

    • ADRs
    • Roadmapping
    • Due diligence
    • Team design
    Deliverables and approach

// architecture preview

Design principles, shown as code.

Three ideas we apply on nearly every engagement. Select one to see how it looks in practice.

Events as the source of truth

Producers publish immutable events; consumers are idempotent and replayable. A bad deploy becomes a replay, not an outage.

ProducersEvent logConsumersRedisPostgresreplayable · idempotent · observable
// Consumer: safe to retry, safe to replay
func (h *Handler) Handle(ctx context.Context, ev Event) error {
    seen, err := h.store.Seen(ctx, ev.ID)
    if err != nil { return err }
    if seen { return nil } // idempotent

    if err := h.apply(ctx, ev); err != nil {
        return fmt.Errorf("apply %s: %w", ev.ID, err) // retried w/ backoff
    }
    return h.store.MarkSeen(ctx, ev.ID)
}

// engagement model

Two ways to work together.

Start with a fixed-scope question, or put senior engineers on your roadmap. Many clients do one, then the other.

Fixed-scope advisory

A defined question, a defined deliverable, a defined price.

Best for

  • Architecture reviews
  • Technical due diligence
  • AI feasibility and build-vs-buy
  • Roadmap and team design

How it works

  • · Scoping call and written statement of work
  • · 2-6 weeks, fixed fee
  • · Workshops with your engineers and stakeholders
  • · Written report and decision records

A document you can act on the day it lands.

Sprint-based execution

Senior engineers shipping alongside your team in short, reviewable cycles.

Best for

  • Building a pipeline or platform
  • Productionising an AI prototype
  • Performance and reliability work
  • Unblocking a delayed roadmap

How it works

  • · Two-week sprints with demos
  • · Shared backlog, your repositories, your CI
  • · Weekly written status, no surprises
  • · Handover docs and pairing in the final sprint

Working software in your environment, and a team that can run it.

Discuss your project