iNexCCo Inc
AI-native product and software engineering
Dallas, TX
inexcco.com · info@inexcco.com
We put AI agents on every stage of your delivery lifecycle, from discovery through operations,
built out of third-party tools you license directly in your own name.
We hold no reseller agreements and take no margin on anything we recommend, which is the
only reason our advice on tooling is worth anything. There's no platform of ours underneath it,
so you can replace any layer without calling us.
System overview — what one request touches
Governance
identity on every call including agent-to-agent · policy-as-code evaluated before the
action runs · guardrails on the prompt going in and the output coming back · a
kill switch that revokes tokens in seconds
01
Surface
A prompt in the IDE, a Slack message, a Jira transition, a webhook.
02
Intake
Normalized, deduplicated, stamped with the caller's identity, committed durably before anything runs.
03
Context
Retrieval across repos, tickets and documents, filtered by what the caller could already see.
04
Model and tools
One gateway in front of every provider. Tool calls execute sandboxed against allow-listed endpoints.
05
Result
Output scanned on the way out, streamed back, the decision written to an audit log.
Where a person gets pulled in. Anything destructive, over budget or below a confidence
threshold stops between 04 and 05 and waits for approval. The workflow is durable, so a pause of
twelve minutes costs what twelve seconds costs, and the approver's name goes in the record next
to the action.
Telemetry
traces scoped to a run across every service it touched · cost attributed to the team
that spent it · answer quality scored against a held-out set · rollback by routing
change, with no rebuild
The eight stages we put an agent on
01
Discover
Ranked opportunities
02
Define
Backlog and criteria
03
Architect
ADRs, contracts, threat model
04
Build
Implementation and migration
05
Assure
Tests and regression
06
Secure
Scanning, agent firewall
07
Release
Pipelines, canary, rollback
08
Operate
Root cause, SLOs, cost
Stage 08 feeds back into stage 01. Nothing merges itself; every change arrives as a pull request a human reads.
The stack, and who owns the license
- ExperienceBackstage · Slack · Jira
- OrchestrationLangGraph · Temporal · Airflow
- Models & toolsClaude · Bedrock · MCP
- GovernanceOpen Policy Agent · Vault · Snyk
- DataKafka · Airbyte · pgvector
- DeploymentKubernetes · Terraform · Argo CD
Common defaults, swapped per engagement. Every license bought by you, at your own rate. Cloud, on-prem, hybrid or air-gapped.
Three things that are actually different
No margin on the advice
We resell nothing. When we tell you a tool is wrong for you, there is no revenue riding on the answer.
The whole lifecycle, not the IDE
A copilot speeds up typing. Writing code was never the slow part, so we cover discovery through operations.
You keep it
Architecture, templates and runbooks go to your team. If you still need us in year three, one of us got this wrong.
What it has moved, and what that means
40–70%
Cycle time removed
wide range, depends on your baseline
2–3×
More shipped per squad
usually visible by month four
6 wks
To first agent in production
if your CI is already green
Zero
Licenses sold by us
you buy your own tools, direct
Ranges from our own engagements. They vary a lot, and the low end is more common on a first
value stream. We measure your actual baseline in week one, before committing to any of these.
When we are the wrong call
We'd rather lose the deal than the first six months. If your builds are red more often than
green, agents will just generate failures faster. If nobody owns the value stream, there's no
one to accept the agents' output and the work stalls in review. Under fifty engineers, the
platform overhead probably isn't worth it and a good copilot license gets you most of the way.
And if what you need is someone to tell the board that AI is happening, hire a consultancy.
They're genuinely better at that than we are.