Durable custom, built like products.
Enterprise custom solutions on Salesforce, AWS, Azure, and GCP. One customer, engineered like fifty: domain models, automated tests, observability, release engineering, sustaining. The full gamut: ideation, design, architecture, build, integration, and the sustain work that starts the day you go live.
Custom builds that outlast the consultants who built them.
Three things that set our Custom Solution Development practice apart.
“Year three is when most custom builds rot. The team that wrote it has rotated, the new team can't read it, and the workarounds start. We write code for the team that inherits it.”
Custom builds deserve the same engineering bar as products.
Custom solutions go to one customer. Products go to many. The shape of the work is different. Your domain, your release cadence, your operators. The engineering bar shouldn't move. The patterns that keep an ISV's product healthy across fifty customer installs are the same patterns that make a bespoke enterprise system last past the consultants who built it: domain modeling, automated tests, observability, release engineering, sustaining. The result is a system your team can still ship from in year five, not another layer on the pile.
We ship on your release cadence
Most consultancies impose a delivery model and let you adapt. We learn how yours works: release windows, testing standards, CAB process, code review culture. We ship inside it. Your engineers release our code the same way they release their own. See how we work →
Same engineers from prototype to operate
The team that designs your architecture is the team that builds it, and the team that builds it is the team that runs it after launch. The senior engineer who scopes the work is in the PRs on day 90. The people who know your domain stay close, and they hand off cleanly to your internal team, with code your team can read.
Custom solutions get the same engineering bar as the products we ship to other companies.
Product builds go to many customers. Custom builds go to one. The shape is different. Your domain, your release cadence, your operators. The engineering doesn't change. Same domain modeling, same tests, same observability, same release pipelines, same sustaining discipline.
From napkin sketch to year-five sustain.
Custom solutions don't ship in one phase. We can plug in at any stage, or run the whole arc end to end. Same pod, same engineers, from the first whiteboard to the on-call rotation that catches the 3am alert.
Ideate
Problem framing, stakeholder alignment, success criteria. Decide what's worth building before anyone scopes the build.
- Discovery and stakeholder interviews
- Opportunity framing and success metrics
- Build / buy / extend trade-offs
- Solution shaping and rough scope
Architect
The shape of the system, settled before the first flow. Domain models, service boundaries, integration patterns, identity, security.
- Domain modeling and service boundaries
- Salesforce or hyperscaler reference architecture
- Integration patterns and event topology
- Identity, security, and compliance models
Design
UX for the operators who'll actually use it. Built with the people whose workday this becomes, not for them.
- Operator journey maps and task flows
- High-fidelity UX and design system fit
- Clickable prototypes for stakeholder validation
- Accessibility and i18n baked in
Build
AI-augmented pods on 1–5 day cycles. PMD plus AI code review on every PR, automated coverage on the flows the business runs on.
- AI-augmented agile delivery
- PMD rulesets and AI code review on every PR
- Automated tests on flows the business depends on
- DX-based CI/CD with reviewable releases
Integrate & implement
ERP, finance, HR, ITSM, marketing, telemetry, identity. The pattern that fits the workload: real-time, batch, or event-driven. Rollout sequenced so the business keeps shipping.
- System integrations (ERP, finance, HR, ITSM, marketing)
- Event-driven backbones and bidirectional sync
- Data migration, cutover, and customer-zero rehearsals
- Change management and rollout sequencing
Sustain
SLA-backed sustaining, regression coverage across releases, incident response. The work that starts the day you go live.
- SLA-backed Tier 3 sustaining
- Release-cycle regression coverage
- Performance, cost, and security optimization
- On-call, incident response, and clean handoff to your team
The work itself is changing every quarter.
AI compounds in months, not years. Models, agents, tooling, and the patterns that work all move faster than any annual roadmap. We work alongside you to spot what's worth adopting, prove it on real workflows, and put what survives into production with the same discipline as the rest of the platform. The output is the workflows and processes themselves, rebuilt to be AI-enabled and agentic by default.
Stay current, ignore hype
Vendors and research labs ship new models, agents, and tooling every week. We track them across the ecosystem and bring you what's worth adopting.
Experiment to production
Sandboxed pilots on real workflows in days, not quarters. Cheap to try, fast to kill the ones that don't pay off. When a pilot proves out, we ship it with the same product-grade discipline as the rest of the platform: tests, eval harnesses, observability, rollback paths.
Workflows, not just features
We rebuild the workflow around what AI makes possible: agents handle the steps machines do better, humans handle the rest, and legacy steps that no longer earn their place come out.
What product ethos looks like on a custom engagement.
Six stages above is the shape of the work. These five practices are the discipline we hold through all of them.
Architecture before customization
Domain models, service boundaries, integration patterns, and security models settled before anyone builds the first flow. The system has a shape, and we defend it across every subsequent feature.
Tests on the things that matter
Automated test coverage on the flows your business runs on, not the boilerplate shipped by default. Regression suites on the integrations that would cost you a quarter if they broke. PMD rulesets and AI code-review agents on every PR.
Observability you'd put in production
Telemetry, error tracking, latency budgets, queue depth, batch-job visibility. The same dashboards you'd put on a SaaS product, pointed at the platform your team logs into.
Release engineering that doesn't ruin Fridays
DX-based CI/CD, scratch orgs, automated promotion across environments, rollback scripts. Permission set deltas, metadata diffs, data migrations: all in the pipeline, all reviewable.
Code your team can own
Opinionated structure, named patterns, documented decisions, decision records you can find six months later. The day we leave, your internal team can read the code, find the why, and ship the next change without us.
The platform is whatever the work demands.
Salesforce anchors many enterprise builds, but plenty live entirely off-platform, or span both. Same pod, same engineering bar, applied wherever the workload fits best.
Salesforce platform builds
Enterprise Salesforce orgs treated as products. Custom objects, flows, Apex, LWC, Data Cloud as the operational anchor for the 500–5,000 people who log in every day. Greenfield builds, classic-to-Lightning rebuilds, monolith decomposition, and consultant-pile cleanup, sequenced so the org keeps shipping while we rebuild underneath it. Specialist-led work sits under Salesforce Solutions.
Internal platforms on hyperscalers
Custom backends and modern web apps on AWS, Azure, and GCP. Serverless where it fits (Lambda, Cloud Run, Functions), containers when it doesn't, React or Next.js front-ends sized to your operators' workflows. Re-platforming and monolith decomposition handled the same way, sequenced so the platform keeps shipping while we rebuild it.
End-to-end business systems
Workflow systems, internal SaaS for ops/finance/CS, forms, approvals, dashboards, process automation. Built for the operators who use them daily, sized for the volume your business runs at, integrated into your identity stack from day one.
Integrations & data backbones
ERP, finance, HR, ITSM, marketing automation, product telemetry, support tooling. Real-time, batch, or event-driven. We pick the pattern that fits the workload. MuleSoft, Workato, Kafka, native APIs. Salesforce Data Cloud, BigQuery, Snowflake, S3, connected to your operational platform without becoming a second source of truth. Heavier pipeline work lives under Data & Integrations.
Internal AI workflows & agents
Agentforce agents pointed inward, at your sales team, your service reps, your operators. Internal copilots, retrieval-grounded assistants, workflow automations that close the gap between the system and the people running their day inside it. Each agent ships with an eval harness and a rollback path before it goes in front of users. Customer-facing agents that ship as products live on Product Development.
Sustaining & operate
SLA-backed Tier 3 sustaining, release-cycle regression coverage, performance and cost optimization, incident response. The team that built it stays close, or hands off cleanly to a dedicated sustain pod. Security controls that ship with the platform sit under Application Security.
Enterprise teams count on us.
A sample of the operational platforms and custom solutions we've built, modernized, and kept running across Salesforce, AWS, Azure, and GCP. We name engagements only with our partners' consent.
“Aquiva has been a trusted partner. Their expertise has brought reliability and extensibility to our platform. What stands out is their proactiveness and eagerness to evolve our systems with high standards.”
Engineering leaderA Fortune 500 work management platform
“You are proactive, responsive, and willing to learn new skills to make our dreams a reality. You make me look good.”
Strategic partnerships leadA leading coaching and development platform
Your custom systems should outlast the consultants who built them.
The platforms running your business should ship like the products your customers love, and keep shipping long after we've gone. Same engineering bar, same observability, same release discipline, the same sustaining muscle.