Fintech and regulated systems
Audit-ready infrastructure, access control design, and p99 performance work for teams where a compliance failure or latency spike has real consequences. We add rigour without adding toil.
Platform engineering
Build systems that stay reliable as your scale and complexity grow.
Karman is an IT consulting firm that helps engineering leaders simplify platform decisions, modernize delivery, and improve runtime reliability across cloud, Kubernetes, and event-driven systems — alongside broader IT consulting for teams that need a trusted technical partner.
40+
platform and modernization engagements
5+
years focused on infrastructure consulting
6
enterprise clients including Siemens and VIAVI
Trusted by teams at
Core capability areas
General IT consultingCloud providersContainer orchestrationMessaging & streamingCloud-native ecosystemsObservabilitySecurityMLOpsDocument intelligenceAI support operations
Service lines
We don't just implement. We help define what the platform should be.
Structured for engineering leadership but technical enough to live inside the codebase — not just in slide decks.
01
General IT consulting & technical advisory
Beyond our platform specialties, we take on broad IT consulting engagements — technology assessments, vendor and tooling decisions, IT operations reviews, and roadmap planning for teams that need a trusted technical partner, not just a niche specialist.
Technology & systems assessmentIT roadmap & vendor strategyOngoing technical advisory
02
Strategic platform consulting
We work with engineering leadership to assess what's broken, define what should change, and sequence the migration — not just produce architecture diagrams that sit in Confluence.
Cloud architecturePlatform baselinesMigration strategy
03
Container orchestration & cloud-native engineering
We help teams move from ad-hoc Kubernetes setups to a real platform — consistent environments, developer self-service, and security controls that don't create a ticket queue.
Orchestration and cluster designPolicy and runtime controlsDeveloper self-service
04
Event-driven & messaging systems
We fix Kafka and event streaming setups that work fine at low volume and start breaking as you scale — topic governance, schema contracts, consumer reliability, replay strategies.
Topology and tenancySchema and contract strategyConsumer reliability
05
DevOps and low-latency execution
We build pipelines teams trust for high-stakes releases and profile systems to move p95/p99 numbers — not just averages.
Release workflowsPerformance engineeringRuntime hardening
06
AI & model engineering
We take models out of notebooks and into production — inference infrastructure, training pipelines, drift monitoring, and audit trails built in from the start.
Model deployment and servingMLOps and observabilityModel governance and monitoring
Industry fit
Strongest where the architecture decisions actually matter.
Karman works best in environments where platform quality has a direct effect on reliability, customer trust, or the ability to close enterprise deals.
B2B SaaS and platform teams
When your product outgrows the delivery setup that got you here, engineering capacity drains into infrastructure. We stabilize the platform, set standards, and get the toil back under control.
Data-intensive product organizations
Event systems, pipeline governance, and storage strategy that scale with your product instead of against it. We design the data infrastructure before it becomes the constraint.
Enterprise software vendors
BYOC deployment, SSO, audit logs, hardened access models — enterprise procurement asks for these before the deal closes. We close the readiness gap without requiring an architecture rebuild.
5+
Years delivering platform and infrastructure consulting
40+
Engagements across cloud, streaming, and MLOps
6
Enterprise clients including Siemens and VIAVI Solutions
2
Products built, shipped, and operated alongside consulting
Products
Platforms we build, ship, and operate ourselves.
Two platforms born from real consulting engagements — ShareDoc for secure document delivery, Resolv for AI-powered support operations — now independently used by teams worldwide.
Document intelligence
Learn moreShareDoc
ShareDoc replaces uncontrolled email attachments with governed, trackable document experiences. Built for teams sending pitch decks, proposals, diligence packs, and board materials where access control and engagement analytics drive the outcome.
72%Less follow-up email
34%Faster deal close
91%Viewer completion rate
Per-recipient links with OTP, SSO/SAML, IP allowlists, and instant revocation
Page-level heatmaps, dwell-time tracking, forward detection, and real-time Slack alerts
Managed cloud, BYOS (S3, Azure Blob, GCS), self-hosted, and private-proxy deployment
The self-hostable alternative to DocSend — with BYOS storage, AI summaries, and no per-seat pricing on viewers.
AI support platform
Learn moreResolv
Resolv unifies support conversations across every channel into one AI-first workspace. Triage, draft, and route automatically — escalate to humans when judgment matters. Priced for growth, not for enterprise lock-in.
60%Faster first response
3×More tickets per agent
1 inboxEvery channel unified
Unified inbox across email, chat, Slack Connect, and in-app channels
AI triage, thread summaries, draft replies, and knowledge-grounded suggestions
SLA tracking, escalation rules, and human-in-the-loop approval workflows
AI native from day one — without Zendesk's legacy overhead, Pylon's CS-hybrid complexity, or SparrowDesk's limited depth.
Representative work
The problems we're usually called in to solve.
Real engagement types, not a brochure. They reflect the situations where Karman is most useful.
General IT consulting for a growing team
Not every engagement starts as a deep platform rebuild. Sometimes it's a broader IT consulting need — tooling sprawl, unclear ownership, a vendor decision leadership can't resolve internally. We come in as a technical advisor first, then go as deep as the problem requires.
- IT systems and tooling assessment with a prioritized action plan
- Vendor and technology roadmap decisions leadership could act on immediately
- A technical advisory relationship that continues past the initial engagement
Resetting a fragmented platform
Most platform problems start the same way: teams building infrastructure separately, cloud setups drifting, no one owning the standards. We reset the foundation — reference architecture, environment standards, day-two runbooks — and hand it off in a state teams can actually maintain.
- Architecture baseline engineering leadership can anchor future decisions against
- Consistent environment and deployment standards applied across all teams
- Runbooks, ownership maps, and operational handoff before the engagement closes
Streaming systems that don't break at scale
Kafka and event systems work fine until the topics multiply, consumers drift, and replay becomes a risk. We impose structure before the complexity becomes unmanageable — or clean it up after it already has.
- Topic hierarchy and schema governance that stays clean as teams and volumes grow
- Dead-letter queues, offset management, and consumer reliability patterns in place
- Lag monitoring, replay playbooks, and incident response runbooks handed off
Enterprise readiness before it blocks a deal
Enterprise procurement is a technical process. Security questionnaires, BYOC mandates, SSO requirements, and audit log requests arrive before a deal closes. We harden the platform for that environment without rewriting the architecture to do it.
- Security posture and access control hardened for enterprise deployment
- BYOC and multi-tenant deployment architecture reviewed and de-risked
- Audit trails, compliance controls, and instrumentation delivered
Engagement model
Structured enough for executive stakeholders. Technical enough for engineering teams.
The goal is usually the same: reduce architectural ambiguity, improve platform quality, and build something the team can maintain after we leave.
Read the system first
Architecture, runtime behavior, release process, team topology. We look at how things actually work before deciding what should change.
Decide what needs to change
We turn goals into a concrete sequence — what to migrate, what to deprecate, what to standardize, and in what order. Not a target-state diagram. A plan someone can execute.
Work inside the codebase
We don't deliver recommendations and leave. We stay on the critical path — reviewing PRs, pairing on infrastructure, validating in production — until the change holds.
Hand off with documentation
Runbooks, ownership maps, architectural decision records. The team should be able to operate and extend what we built without calling us.
It all starts with a conversation.
Platform reviews, architecture consulting, ShareDoc or Resolv demos — or just a scoping call.