From clear
to working software.

Senior engineers and specialized AI agents turn business goals into tested, released software. Clear scope. Visible progress. Human accountability — at production speed.

human-owned intentagent executionevidence, not claims
our delivery approach
01
Business goalHUMAN
Why, for whom, what outcome
02
Specs & tasks graphMODELS
Frontier models, approved with you
03
OrchestrationAGENT
Lead agent plans the run
04
ImplementationSUB-AGENTS
A fleet of dev agents, task by task
05
Code reviewAGENTS
Automatic, findings loop back
06
Regression & new testsAGENTS
Other agents verify behavior
07
Verify & releaseHUMAN GATE
Human acceptance, included in release
gate: human approval↻ monitored · measured · improving

pilot targets — measured against our human+ai baseline

−50%
time from intent to accepted change
vs. human+ai baseline
15 min
human review per accepted change
target, minutes not hours
70%
tasks completed without intervention
blocked work escalates
100%
changes fully traceable
goal → spec → pr → release

accountability map

People own the decisions.

Agents generate code, but humans own the outcomes. Every critical checkpoint has a named, accountable owner.

You — the Customer

Provides the business context and goals. Approves the initial technical brief and accepts the final verified release.

owns business intent

Delivery Manager

Translates your intent into strict briefs. Ensures scope is maintained and verifies that final outcomes match acceptance criteria before presentation.

owns scope & outcome

Engineering Lead

Designs the architecture and guides agent execution. Reviews generated code for security, performance, and adherence to system patterns.

owns technical quality

commercial model

Capacity Pods, not billable hours.

We abandoned archaic Time & Materials. You subscribe to a ready-made quantum of production capacity — a Capacity Pod — with a guaranteed SLA. Predictable cost, no timesheets, no token meter.

Symbion Trio

starter pod

1 Senior Lead2 Virtual Developers

focus

  • →Mid-level backlog tasks
  • →Legacy module refactoring
  • →End-to-end test coverage
  • →Isolated microservices

sla

  • ✓First pull request in 48 hours
  • ✓Intake task scoring within 24 hours

Fixed monthly subscription

Request a quote

Symbion Quad

most teams start here

primary production pod

1 Tech Lead / Architect3 Virtual Developers

focus

  • →Critical product features from scratch
  • →Architecture of new systems
  • →Database & key service migrations

sla

  • ✓Up to 4 parallel working sessions in your repository
  • ✓Guaranteed uptime

Fixed monthly subscription

Request a quote

Symbion Fleet

enterprise scale

2–3 Lead Architects8–12 specialized virtual agents

focus

  • →Replaces a classic 15–20 person outsourced department
  • →Integration with local models

sla

  • ✓Dedicated Forward-Deployed Engineer
  • ✓Individual compliance audits

Custom contract · on-premise deployment available

Request a quote
pod live in 48–72 hoursno time & materials · no token metercontext stays in the platform, not in people's heads

operating model

One human lead.
Specialized agent execution.

A senior developer leads the work, sets priorities and architecture, and reviews outcomes. Agents use the right skills and project context for each task — and every blocker returns to the lead.

human ownership
You + Delivery Manager
business context, priorities, final say
· sets direction
· reviews outcomes
agent 01
Business Analysis Agent
turns conversations into specs
· asks clarifying questions
· drafts specs with you
approved specs & tasks graph
agent 02
Planning Agent — Orchestrator
composes the run and launches the fleet
breaks work into tasks · assigns context · spawns sub-agents per artifact
launches a fleet, scaled to the work
development sub-agents · created in batchesmany, per artifact type
frontend
× n tasks
backend
× n tasks
data
× n tasks
mobile
× n tasks
integration
× n tasks
docs
× n tasks

each sub-agent takes one task and implements it end to end

changes flow forward, findings flow back
agents 03
Code Review
automatic review on every change
agents 04
QA & Regression
new tests written by other agents
agent 05
Release Agent
composes release + evidence
↩results and blockers return to the lead — nothing ships unseen

where decisions live

Human Decision

the exclusive prerogative of people

  • →Business value judgment — what is worth building and why
  • →System decomposition and specification of goals → initiatives
  • →Architecture trade-offs and hard boundaries
  • →Domain semantics and final say on how goals are achieved

AI Assist

synthetic agent power

  • →Parallel boilerplate and template code generation
  • →Environment scaffolding and deployment setup
  • →Exhaustive test generation against acceptance criteria
  • →Syntax analysis and repository style compliance

one senior's engineering reach grows 5–10× — without burnout or loss of focus

why symbionsquad

More than code.
A complete delivery process.

Controlled environments

Every run happens in an isolated, reproducible environment. Configuration is recorded for each important result — failures are attributable, results are repeatable.

Full traceability

Every change carries a reason: goal → spec → task → code → tests → release.

Human in the loop

Business acceptance and high-risk changes stay with people. Agents escalate; they never self-approve.

Adversarial verification

An isolated QA-hunter agent assumes the implementer's code is defective — stress tests, network failures and edge cases run in real dev environments. You get proven behavior, not claims.

Reusable knowledge

Guides, templates, skills and architecture rules become versioned project assets — not folklore.

Measurable delivery

Time to accepted change, human minutes, rework cycles, escaped defects — the pilot is judged on numbers.

Predictable cost

You buy accepted outcomes, not tokens — model choice and infrastructure are priced into delivery, not metered on your invoice.

why symbionsquad

Symbiosis, not the illusion of autonomy.

The market is polarized between archaic outsourcing and unstable autonomous agents. We occupy a different niche: deterministic symbiosis. An experienced engineer sets the intent and hard architectural boundaries — agents deliver the routine code generation. That is Human Amplification.

SymbionSquad

deterministic symbiosis

Architectural accountability

A named senior owns the architecture. Code leaves the squad only after human review against system context and security standards.

What you receive

Verified, reviewed changes with full test evidence — ready to merge without overloading your own staff.

Commercial model

A fixed monthly subscription per capacity pod. No rate cards, no timesheets, no metered tokens.

Time to start

Pod live in 48–72 hours. Domain context is fixed in the platform's context graph — not in people's heads.

How you scale

Add agents to the pod. One senior's engineering reach grows 5–10× without burnout.

Autonomous agent platforms

the illusion of autonomy

Architectural accountability

Agents produce code but cannot carry architectural accountability for the long-term evolution of the system.

What you receive

Unvalidated diffs your senior engineers must re-read — the review bottleneck burns out your team.

Commercial model

Seats, tokens and opaque compute fees that scale with usage, not with outcomes.

Time to start

Instant to start, ungoverned to run. Every extra agent adds review load on your side.

How you scale

More agents means more code to verify — the speed gain collapses at review time.

Classic outsourcing

archaic time & materials

Architectural accountability

Accountability depends on who is still staffed on your project this quarter.

What you receive

Billed hours. Quality and velocity vary with every staffing change.

Commercial model

Time & Materials — you carry the risk of every estimate miss.

Time to start

2–6 months of hiring and onboarding before the team becomes productive.

How you scale

Scaling means recruiting and retaining — domain context leaves with every departure.

human amplification — your engineers become conductors, not code typists

illustrative workflow

Adding role-based approvals

A real-shaped slice of the protocol: from a business sentence to test evidence — nothing ships on the agent's word alone.

sq-1042 / role-based approvals accepted
1Business requesthuman
"We need a way for managers to approve large refunds in the internal dashboard before they are processed."
2Acceptance criteriahuman gate
—Refunds over $500 require user with 'manager' role to approve.
—Approval state must be logged with timestamp and user ID.
3Verification evidenceagents + ci
test_standard_user_cannot_approve_large_refund
test_manager_can_approve_large_refund
test_approval_audit_log_created
4Adversarial QA runadversarial agent

assumes the implementer's code is defective · isolated from the author

test_network_timeout_during_approval
test_concurrent_approvals_no_double_refund
test_approval_survives_service_restart
traceable: intent #a41f → release #42aagate passed: customer acceptance

start here

Start with one meaningful change.

Choose a scoped task. We agree on success criteria, execute through our process, and evaluate the result together.

  • →Define a specific problem
  • →Review the test evidence
  • →Decide on next steps

pilot scope: one project · one stack · one vertical slice

Discuss a pilot

we reply within 2 business days