When packaged platforms don't fit, we engineer tailored stacks on open formats and modular components. High performance, low licence cost, full ownership of your IP and infrastructure. Pick what you need at every layer — extraction, storage, compute, transformation, visualization — and swap any of it later without a migration.
Off-the-shelf data platforms are great — until they aren't. Three signals you've hit the wall, and a different way to build past them: on open formats, with components you actually own.
Per-user licences and tier upgrades to unlock one connector. Six-figure renewals on a platform that runs three dashboards. The bill scales with users, not with value delivered.
Custom calculations bolted on with macros. Integrations duct-taped through CSV exports. The product roadmap doesn't care that your business model is one-of-one.
Proprietary file formats, closed APIs, no way to leave without rebuilding from scratch. Every renewal feels like a hostage negotiation. There is another way.
Bespoke doesn't mean snowflake. Every engagement starts from the same set of architectural commitments — open standards, modular components, your IP, your cloud — then bends to fit the workflow you actually have.
Custom APIs and pipelines that fit your processes, not the other way around. Connect ERPs, CRMs, data platforms, and SaaS — across cloud and on-prem — with code you can read.
Modern engines — DuckDB, Trino, Polars — on Parquet and Iceberg. Sub-second queries, columnar everything, no warehouse credit meter ticking in the background.
Pay for compute and storage, not per-user seats or arbitrary SaaS tiers. Open-source core. The bill scales with workload, not your headcount.
Open formats — Parquet, Iceberg, Delta. Open standards — SQL, Python, REST. Swap any component without rebuilding. The exit ramp is a feature, not a fight.
On-prem, private cloud, or hybrid. RBAC, encryption at rest and in transit, audit logs, retention policies. SOC 2, GDPR, HIPAA — designed in, not bolted on.
Predictive models embedded directly in dashboards and operational apps. Feature engineering, deployment, monitoring — your team gets recommendations in their workflow, not in another tool.
Microsoft .NET backends, Flutter and Swift mobile, React/Next on the web. Not a dashboard wrapper — a real product, branded, with its own UX and offline modes.
AWS, Azure, GCP, on-prem, or all of the above. The architecture moves with you. Lift-and-shift across providers without rewriting the data layer.
The myth survives because "proprietary = secret = safe" feels intuitive. It isn't. Closed source means a vendor's security team reviews the code; open source means everyone's security team reviews it — academic researchers, every Fortune-500 SecOps group, governments, and adversaries. Bugs surface in days, not at the next vendor disclosure window. The components in our reference stack — Postgres, dbt, DuckDB, Polars, Iceberg, Linux — run the production infrastructure at most banks, every hyperscaler, the CIA, and the IRS.
No black boxes. Your security team can audit, fuzz, fork, or patch any component. Try that with a closed SaaS — even your CISO can't see what their CVE response actually changed.
Critical CVEs in mainstream OSS typically have public patches within hours of disclosure. You don't wait for a vendor's quarterly release train or pay-tier support contract to get a fix.
Self-hosted means data never leaves your VPC. No third-party telemetry, no support engineer with break-glass access, no vendor breach that quietly includes your data. Air-gap it if you need to.
SOC 2, GDPR, HIPAA, PCI, FedRAMP-aligned — we've shipped all of them on open-stack components. RBAC, encryption, audit logs, retention. It's a checklist, not a barrier.
Pick the components you need at every layer. Each row provides multiple interchangeable options on open formats and protocols — no proprietary lock-in, just flexibility and full control. Swap any tile later without rebuilding.
Custom doesn't mean unpredictable. Every engagement runs on the same five-phase rhythm — discovery, design, build, hardening, handover — with milestones and exit criteria the engineering team can hold themselves to.
Workflows, data sources, current stack, constraints. Define what success looks like in writing. Stack-selection workshop: pick your tiles, document the trade-offs.
Reference architecture sized to your volume. Data contracts. Security review and threat model. Cost projection vs the platform you'd otherwise renew.
Pipelines, models, dashboards or apps — built in your repo, in your cloud. Pair-programmed where you have engineers; fully owned where you don't.
Load tests, failover drills, observability, runbooks. Security and compliance sign-off. UAT with real users on real data.
Documentation, knowledge transfer, monitoring dashboards. Optional managed-ops retainer or full handover to your team. We stay on call either way.
Bespoke engagements deliver more than a working system. Here's what stays with you when we hand over the keys — the strategic advantages of building open and modular instead of buying packaged.
Pay for compute and storage, not seat licences. Open-source core means licence costs trend toward zero as you scale. Most clients see a 60–80% drop vs the platform they were renewing.
Sub-second queries on multi-billion-row tables with DuckDB or Trino on Parquet. No warehouse credit meter, no unpredictable autoscale bill at end of month.
Code in your repos, data in your buckets, models in your registry. No "platform IP" clauses, no escrow theatre. If we disappeared tomorrow, your stack runs on Monday.
Want to swap dbt for SQLMesh? Trino for Snowflake? Metabase for Power BI? Each layer is replaceable in isolation. The cost of changing your mind is bounded.
Open standards mean your engineers can hire, learn, and extend on the same skills that show up on every résumé — Python, SQL, Parquet, dbt. No proprietary certifications required.
A custom engineering engagement scoped to your workflow, your stack, and your constraints. We bring the architecture, the senior engineers, and a track record of shipping. You bring the problem.
Engagements scoped per workflow / data volume. Fixed-price options available for proof-of-concepts and discrete builds; T&M for embedded teams. No licence fees on open-stack components.
The questions we get most often during scoping calls. If yours isn't here, write to info@arkimetrix.com.
Packaged platforms optimize for the average customer — they bundle features so the bill works, and they shape your workflow to fit theirs. A custom build is the opposite: we pick only the components you need, in formats you control, and shape the system around how your business actually works. The trade-off is upfront engineering effort vs ongoing licence fees and configuration tax. For most businesses past a certain volume, the math flips quickly toward custom.
Three reasons. (1) Cost — core components like dbt, DuckDB, Polars, Postgres, Metabase, and Superset have $0 licence cost; you pay only for compute, storage, and our engineering. (2) Talent — these are the skills on every data résumé, so your team can hire and grow without proprietary certifications. (3) Longevity — open formats (Parquet, Iceberg, Delta) and open protocols (SQL, REST) mean your data is readable in 10 years without us, without the vendor, without anyone.
Three deployment patterns, your call. (1) Your cloud — everything runs inside your AWS / Azure / GCP tenant; we get scoped access to build and hand back. (2) On-prem — full stack inside your data centre, air-gapped if needed; common in financial services and regulated industries. (3) Arkimetrix managed — dedicated tenant on our SOC 2-aligned infrastructure for clients who don't want to operate the platform. DPAs, retention policies, and data-flow diagrams in every pattern.
Yes, by design. The whole stack is built on open standards and code your engineers can read — Python, SQL, dbt, Parquet. We deliver runbooks, architecture docs, and a knowledge-transfer programme as part of every engagement. Most clients keep us on a light retainer for the first six months and then run independently. Some keep us as an ongoing partner because they want to; none because they have to.
Compliance is designed in, not bolted on. RBAC at every layer, encryption at rest (AES-256) and in transit (TLS 1.2+), structured audit logs, configurable retention. We've delivered systems meeting SOC 2, GDPR, HIPAA, and PCI requirements; we'll align to whichever regime you operate under. Threat-model and security review are line items on the project plan, not afterthoughts.
A two-week paid discovery, fixed price. By the end you have: a reference architecture, a build plan, a cost projection (build + run-rate vs your current spend), and a fixed-price quote for the build itself. If you don't proceed, you keep the discovery deliverables. If you do, the discovery cost rolls into the build. Most builds run 8–14 weeks; longer engagements break into milestoned phases with go/no-go gates.
Toronto, Canada and Pune, India. One team, two time zones. Most clients see this as a feature, not a bug — coverage runs nearly around the clock, and the cost structure lets us field senior engineers on engagements where bigger consultancies would default to juniors.
A 30-minute technical discovery. Bring the workflow you can't get a packaged platform to handle, the renewal that's about to triple, or the prototype that needs to become production. We'll come back with an architecture sketch and a build plan within a week.