Agentic workflows
Multi-step agents that act in your systems through APIs and MCP, with approval gates where money or customers are involved.
Now taking projects for Q4 2026
We turnideasintosystems.
An AI-native engineering studio. We design, build and ship AI agents, digital products and the cloud behind them — production-ready from the first release.
- TypeScript
- React
- Next.js
- React Native
- Node.js
- Python
- LangGraph
- Claude
- OpenAI
- MCP
- pgvector
- Postgres
- AWS
- GCP
- Kubernetes
- Terraform
The thesis
Commercial reality > tech theater.
Technology should move your business forward, not slow your team down.
We build multi-tenant SaaS platforms, AI workflows that take real actions, and cloud systems that stay up under load. No throwaway demos — software that earns its keep.
Services
What we
build.
Four disciplines, one senior team. Most projects combine two or more.
01AI agents & automationAgents that do real work inside your tools — support triage, document processing, ops workflows — with evals, guardrails and human review built in.LangGraphClaudeOpenAIMCPpgvector
- Pick the workflowFind the task where automation pays back fastest.
- Real data, fastWorking agent on your data in days, not months.
- Evals & guardrailsTest suites, approvals and fallbacks before launch.
- Ship & monitorTracing, cost dashboards and continuous tuning.
02Web & mobile productsSaaS platforms, customer portals and mobile apps — type-safe, tested and production-ready from the first commit.TypeScriptNext.jsReact NativeNodePostgres
- Scope & specUsers, data model and the smallest valuable release.
- UX & design systemFlows and components your team can extend.
- Weekly releasesWorking software every week, behind feature flags.
- Measure & iterateAnalytics, error tracking and a roadmap for v2.
03Cloud & DevOpsInfrastructure as code, CI/CD, Kubernetes and observability — so you can ship daily without 3 a.m. pages.AWSGCPTerraformKubernetesGitHub Actions
- Cost & risk reviewWhere you're overspending and what breaks first.
- Infra as codeReproducible environments, reviewed like app code.
- CI/CD pipelinesZero-downtime deploys and instant rollbacks.
- Monitoring & SLOsAlerts that matter, dashboards people read.
04Data & integrationsConnect ERPs, CRMs and legacy systems. Event pipelines, durable workflows and dashboards your team actually uses.KafkaTemporaldbtClickHouseREST / gRPC
- Source systemsReliable syncs from the tools you already run.
- Clean data layerOne trustworthy source for reporting and AI.
- Durable workflowsRetries, idempotency and audit trails by default.
- Dashboards & alertsDecisions from data, not spreadsheets.
AI engineering
AI isn't a feature.It's a new layer.
Most AI projects stall after the demo. We build the parts that make it work in production: clean data access, evaluation, guardrails, cost control — and a human in the loop where it matters.
How production AI fits together
- Your dataDocs, DBs, tickets, events
- RetrievalPermission-aware search
- ModelsFrontier or open-weight
- AgentsPlan, act, self-check
- ToolsAPIs, MCP, approvals
- OutcomeMeasured, logged, owned
AI inside your product
Copilots, semantic search and assistants embedded in the product your customers already use.
RAG you can trust
Answers grounded in your documents and databases, with citations and per-user access control.
Evals, guardrails & cost
Automated test suites, red-teaming, tracing and spend dashboards so quality doesn't drift after launch.
Selected work
We build
real things.
Our client work runs under NDA, so names stay private. We'll walk you through architecture and results on a call.
Client names under NDAReconciliation agent for a finance ops team
Reads invoices and bank statements, matches them against the ledger and routes only the exceptions to a human reviewer.
- Python
- LangGraph
- Postgres
- AWS
Real-time dispatch console
Live operations dashboard for dispatchers with offline-first mobile companion app for drivers in the field.
- Next.js
- React Native
- Node
- Redis
Multi-region platform migration
Moved a monolith onto Kubernetes with Terraform-managed infrastructure, blue/green deploys and full observability.
- AWS
- Terraform
- Kubernetes
- Grafana
Clinical knowledge assistant
Permission-aware search over internal guidelines and records, with cited answers and an audit trail for every response.
- TypeScript
- pgvector
- Claude
- GCP
Process
From brief
to production.
Weekly demos, working software, no black box. You see progress every week.
- 011–2 weeks
Discover
Workshop your bottleneck, map data and constraints, agree on what success looks like.
- 021–2 weeks
Design
System architecture, API contracts and UX flows — reviewed with your team.
- 03Weekly releases
Build
Weekly demos of working software. AI features ship with evals from day one.
- 04Ongoing
Ship & scale
Zero-downtime launch, monitoring, then iterate — or hand over cleanly to your team.
Ways to work with us
Best place to start2–3 weeks
AI Sprint
Pick one workflow. We ship a working AI prototype on your real data, plus an eval report and a go / no-go plan.
Discuss AI SprintOption 026–12 weeks
Product Build
A scoped MVP or new platform, designed and shipped to production by a senior team.
Discuss Product BuildOption 03Monthly
Dedicated Team
An embedded pod of engineers and a tech lead shipping alongside your team.
Discuss Dedicated TeamWhy GR8SPARK
A small senior team. Not a body shop.
You work directly with the engineers building your system — no account managers relaying messages, no junior bench learning on your budget.
- 01
Commercial purpose first
Every feature has to move a number — revenue, cost, or time. If it doesn't, we'll tell you.
- 02
AI where it earns its place
We use AI when it clearly beats the alternative, and say so when a plain workflow is the better answer.
- 03
Production from day one
Typed code, tests, CI and monitoring from the first commit. No throwaway prototypes.
- 04
You own everything
Code, infrastructure and documentation are yours. Clean handover whenever you want it.
FAQ
Straight
answers.
Can we sign an NDA before we talk?
Yes. Most of our work is under NDA, and we're happy to sign yours before the first call.
Can we see your past work?
Our client work is confidential, so it isn't published here. On a call we walk through relevant projects, architecture and results in detail.
Who owns the code?
You do. All code, infrastructure and documentation transfer to you — no lock-in.
Do you work with our existing team and codebase?
Yes. We regularly join existing products, pair with in-house engineers and follow your conventions.
Which AI models do you use?
We're model-agnostic: frontier APIs such as Claude and GPT, or open-weight models you host yourself — chosen per use case for quality, latency, cost and data-privacy needs.
How quickly can you start?
Usually within two weeks of agreeing scope. An AI Sprint can often start sooner.
Start a project
What are youbuilding?
Tell us about the bottleneck. We'll reply within one business day with next steps — or a straight answer if we're not the right fit.