You may have a business objective, a detailed specification, or a system already in production. We meet you there.
You bring the business objective. We help prioritize the use case, define success, and design and deliver the solution.
Start with discovery, test a focused pilot against your baseline, then scale on evidence.
Build from scratch
Validate your idea and launch a first product customers can use reliably.
Typical track: 8–16 weeks, subject to scope
Explore Zero-to-One ↗Scale-up engineering
Help a growing product team deliver faster with a platform it can maintain and extend.
Phased engagement around agreed improvements
Explore platform engineering ↗Automate a workflow
Move repetitive work into an AI agent with clear limits and measurable business value.
Pilot first; expand after measured results
Explore agentic AI ↗You bring the product vision or specification. We validate assumptions and implement them against agreed acceptance criteria.
Commission a focused implementation, a capability installation, or repairs to an existing setup. A wider transformation is optional.
Product implementation
Turn an agreed product scope or AI workflow into software your team can operate.
New product, AI feature or production agent
Discuss your specification ↗Scale-up engineering
Harden a working AI-built prototype for real users, data and production demands.
90-day track, subject to audit and agreed scope
Explore Vibe-to-Scale ↗Engineering capabilities
Fix unreliable agent behavior or add the checks needed to release AI with confidence.
Installed or remediated in your environment
See technical deliverables ↗Keep what works.
Strengthen what holds you back.
We start by testing existing behavior and identifying the changes your next release needs. The assessment documents what to retain, repair or replace, so you can review the scope before implementation.
Our evidence-based delivery framework connects what you asked for to what was built, checked and approved.
Starting point: shoppers knew they needed a gift, but not what to search for.
Work: an AI assistant that interprets intent and guides gift discovery.
Prototype in 3 days; about 6 weeks from first demo to A/B testing. The case reports conversion uplift; the test sample and measurement window are not published.
Starting point: off-hours incidents interrupted a team working across time zones.
Work: an agent investigates issues and opens fixes for human review.
65–70% of incidents resolved correctly without rework. Code never auto-merges. Deployment follows human review; the reporting period is not published.
Starting point: an online store needed support that could handle waves of customer questions.
Work: an AI chatbot connected to business data on autoscaling infrastructure.
Reported 100% uptime during peaks of 30 requests per second. These are case-specific results; the observation period and pre-project baseline are not published.
Harness Engineering controls how agents work. Eval Engineering checks whether their behavior and outputs meet your standard.
For teams seeing inconsistent results, ignored conventions or agents with access they should not have.
What your team receives
— Versioned rules and AGENTS.md instructions
— Tool and MCP access, sandbox boundaries and hooks
— Model routing, orchestration and autonomy settings
— Documentation to operate and extend the setup
For teams whose demos look good, but whose production quality is hard to measure or changes with the model.
What your team receives
— Real scenarios and explicit scoring rubrics
— Output and trajectory evals, including model judges where appropriate
— CI release gates alongside deterministic tests
— A maintenance path as models and requirements change
A named phase of the build; inherited by your team at handover.
A standalone, fixed-scope engagement with documentation and handover.
An audit-led engagement for an existing setup that is not behaving reliably.
Sara Lufrano
Principal Technical Product Manager, Space Needle
Always delivered on time. Highly responsive to our needs. 10/10.
Start with a free intro call. If a deeper review is useful, we agree the scope and fee for an AI Production Readiness Review.
Your starting point: Define the solution together
Scope, fee, team and turnaround are agreed before the paid assessment.
It is SPD Technology’s engineering service. Our team designs and delivers software and AI systems, or installs specific engineering capabilities in your environment. It is not a software subscription you need to adopt.
Yes. Choose “Deliver against your direction.” We validate assumptions, agree acceptance criteria and implement the scope. You do not need to buy a transformation program first.
We assess what can be retained and where targeted changes are needed. We test current behavior before changing existing code. Any proposed replacement is explained in the assessment; retention depends on your system and requirements.
The free intro call establishes fit. An AI Production Readiness Review is a paid technical assessment, with scope, fee and turnaround agreed before it begins. Standalone capability installations use a fixed scope; the delivery proposal sets the team, milestones, commercial model and acceptance criteria. No universal price or team size applies to every project.
We agree your baseline and success measures before the pilot. Depending on the work, these may include conversion, manual effort, time to a verified release, incident rates, operating costs or cost of change. Pilot results inform the decision to expand.
The code, specifications, tests, agent configuration, eval suites and operating documentation remain in your repository. Ownership and handover obligations are written into the engagement contract.