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Services

Technology services built around your business.

SynapseSoft provides flexible software engineering and technical consulting. Engage us for a full product build, a specific technical problem, or additional capacity alongside your existing team.

01

AI Training & Evaluation

RLHF, model evaluation, red-teaming, and expert-generated training data — produced by specialists qualified in the domain being evaluated, against rubrics designed for your task.

Typical challenges

  • Benchmarks look fine but users still hit the same failure mode
  • Annotators disagree and nobody can say which of them is right
  • General-purpose labeling misses errors only a specialist would catch

What we provide

  • Rubric design, calibration sets, and annotator screening
  • Preference data, rankings, and written rationales for reward modeling
  • Adversarial testing and structured evaluation against your criteria
  • Agreement metrics and audit results delivered with the data

Technologies we commonly use

  • Python
  • OpenAI
  • Claude
  • Gemini
  • PyTorch
  • AWS

02

Software Development

End-to-end development of web, mobile, and internal applications — from the first architecture decisions through to a system your team can keep changing safely.

Typical challenges

  • Releases slow down as the codebase grows
  • Features are hard to change without breaking something else
  • The original build was outsourced and is now undocumented

What we provide

  • Product and technical discovery before any code is written
  • Application development in short, reviewable increments
  • Code review, documentation, and handover your team can work from
  • Performance, accessibility, and security work as part of delivery

Technologies we commonly use

  • React
  • Next.js
  • TypeScript
  • Node.js
  • Python
  • .NET
  • PostgreSQL

03

SaaS Development

Multi-tenant products built with the parts that are easy to postpone and expensive to retrofit: tenancy, roles, billing, onboarding, and operational tooling.

Typical challenges

  • A prototype needs to become a product real customers can pay for
  • Tenant isolation and permissions were not designed in from the start
  • Support and billing questions consume engineering time

What we provide

  • Multi-tenant architecture and data model design
  • Authentication, roles, permissions, and audit trails
  • Subscription billing, plans, usage limits, and trials
  • Admin tooling so support does not require a developer

Technologies we commonly use

  • Next.js
  • Node.js
  • PostgreSQL
  • Redis
  • AWS
  • Docker

04

AI Solutions

Practical AI features inside real products — built with evaluation and guardrails, so you can tell whether they actually work before your customers do.

Typical challenges

  • It is unclear which AI use cases justify the cost
  • A demo works, but quality is inconsistent in production
  • There is no way to measure whether the output is good

What we provide

  • Use-case assessment with an honest view of what AI will not solve
  • LLM features: retrieval, structured extraction, assistants, classification
  • Evaluation sets, quality monitoring, and guardrails
  • Cost, latency, and model-selection trade-off analysis

Technologies we commonly use

  • OpenAI
  • Claude
  • Gemini
  • LangChain
  • Python
  • PyTorch
  • TensorFlow

05

Business Automation

Connecting the systems and manual steps your business already runs on, so work moves between them without someone copying data by hand.

Typical challenges

  • Critical processes live in spreadsheets and email threads
  • The same data is re-entered into several systems
  • Nobody can say where a request currently is

What we provide

  • Process mapping and a realistic automation plan
  • Integrations between CRM, finance, support, and internal tools
  • Scheduled jobs, queues, and event-driven workflows
  • Internal dashboards and status visibility

Technologies we commonly use

  • Node.js
  • Python
  • PostgreSQL
  • Redis
  • Azure
  • AWS

06

Technical Consulting

Architecture, technology strategy, and engineering guidance — for the decisions that are cheap to make early and costly to reverse later.

Typical challenges

  • A major technical decision is blocking the roadmap
  • The team disagrees on the direction and needs an outside read
  • You need a technical opinion before committing budget

What we provide

  • Architecture and codebase review with written findings
  • Technology selection and build-versus-buy analysis
  • Scalability, cost, and risk assessment
  • Roadmap and delivery planning with your engineering leads

Technologies we commonly use

  • AWS
  • Azure
  • Google Cloud
  • Kubernetes
  • Terraform
  • PostgreSQL

07

Cloud & DevOps

Environments, pipelines, and observability that make deployment routine — plus the cost controls that keep infrastructure spend explainable.

Typical challenges

  • Deployments are manual, risky, and only one person can do them
  • Cloud costs are rising without a clear reason
  • Outages are found by customers rather than by monitoring

What we provide

  • CI/CD pipelines and repeatable environment setup
  • Infrastructure as code and reproducible provisioning
  • Monitoring, logging, alerting, and on-call runbooks
  • Cost review and right-sizing

Technologies we commonly use

  • AWS
  • Azure
  • Google Cloud
  • Docker
  • Kubernetes
  • Terraform
  • CI/CD

08

Engineering Support

Experienced engineers added to your existing team, working in your process and tooling, sized to what the roadmap actually needs.

Typical challenges

  • Hiring is taking longer than the roadmap allows
  • The backlog is clear but there is no capacity to work it
  • Maintenance is crowding out new development

What we provide

  • Engineers embedded in your workflow, standups, and code review
  • Flexible capacity that scales with project requirements
  • Maintenance, dependency upgrades, and bug work
  • Knowledge transfer and documentation as standard

Technologies we commonly use

  • React
  • Vue
  • Angular
  • Node.js
  • Python
  • PHP
  • Laravel
  • .NET

09

QA & Testing

Automated coverage and release checks that turn deployments from an event into a routine, and catch regressions before your users report them.

Typical challenges

  • Every release needs a manual regression pass
  • Test coverage exists but nobody trusts the suite
  • Bugs reappear after they were supposedly fixed

What we provide

  • Unit, integration, and end-to-end test suites
  • Test automation wired into CI with meaningful failure signals
  • Regression, performance, and accessibility testing
  • Release checklists and quality gates

Technologies we commonly use

  • TypeScript
  • Python
  • CI/CD
  • Docker
  • PostgreSQL
  • AWS

Everything else

The full list of what we can take on.

If what you need is not listed here, ask anyway — we will tell you honestly whether it is a fit.

RLHF & Preference Data

Response comparisons, rankings, and rationales produced against a calibrated rubric.

Model Evaluation

Structured scoring on criteria you define, delivered with agreement metrics and disagreement cases.

Red-Teaming

Adversarial prompting to surface jailbreaks, harmful completions, and brittle reasoning.

Expert Data Generation

Prompts, reference answers, and worked solutions written by people qualified in the field.

SaaS Development

Multi-tenant products with billing, roles, onboarding, and the operational tooling behind them.

Web Applications

Responsive, accessible applications built on modern frameworks and a maintainable component layer.

Mobile Applications

Cross-platform and native mobile apps that share a backend with your existing product.

AI Integration

LLM features, retrieval, evaluation, and guardrails wired into real product workflows.

Business Automation

Internal processes connected end to end so manual handoffs stop consuming your team's time.

API Development

Versioned, documented APIs and integrations between the systems your business already runs.

Cloud Infrastructure

Environments, networking, cost control, and observability across AWS, Azure, and Google Cloud.

System Modernization

Incremental replacement of legacy components without pausing delivery on the current product.

Technical Architecture

Data models, service boundaries, and scaling decisions documented before they become expensive.

Testing & QA

Automated coverage, regression suites, and release checks that make deployments predictable.

DevOps & Deployment

CI/CD pipelines, infrastructure as code, and repeatable deployments across environments.

Ongoing Engineering Support

Maintenance, monitoring, dependency upgrades, and steady improvement after launch.

Next step

Not sure which service you need?

Describe the problem in your own words. We will tell you what it would take to solve it, and whether we are the right team for it.