Software built around your problem,
not the other way around.
Domain-tuned models, agent systems, eval harnesses, and the data pipelines that hold them together — engineered with mission-critical rigor and shipped under your IP.
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Operations summary across every custom ai software module deployed in your tenant — last 24 hours.
- Engagements 5 Live
- Models 24 Live
- Evals · CI 142 Live
- Builds 142 Live
- Pipelines 24 Live
- Handover 4 Live
- 14:45 Engagements ON TRACK ENG-049 · Legal review pipeline — Phase 3/4 · hardening
- 14:38 Models PROD agaro/legal-review-7b — fine-tuned · ENG-049
- 13:31 Evals · CI PASS legal-review · safety — 482/482 · 0 regressions
- 13:24 Builds PASS agaro/operator-console#1840 — staging deploy
- 12:17 Pipelines LIVE legal-rag · ingest — 4,128 docs/d
- 12:10 Handover CLOSING ENG-047 · Claims triage — 90% transferred · pair wk 12
Engagements
Discovery → prototype → hardening → transfer. Every engagement runs the same four-phase rhythm.
// Engagements
// Discovery → prototype → hardening → transfer. Every engagement runs the same four-phase rhythm.
export const engagements = {
live_engagements: '5',
avg_cycle: '14 wks',
on_schedule: '5/5',
handover_90d_tail: '4 active',
};
- ✓ ENG-049 · Legal review pipeline Phase 3/4 · hardening wk 9 of 12
- ✓ ENG-048 · Underwriting agent Phase 2/4 · prototype wk 6 of 14
- ✓ ENG-047 · Claims triage Phase 4/4 · transfer 90d tail
- · ENG-046 · Field dispatch Phase 1/4 · discovery wk 2 of 16
Models
Fine-tuned, distilled, and adapter-trained models in registry — including parameter-efficient methods that fit your inference budget.
// Models
// Fine-tuned, distilled, and adapter-trained models in registry — including parameter-efficient methods that fit your inference budget.
export const models = {
models_in_registry: '24',
adapter_sets: '142',
avg_inference: '142ms',
ip_ownership: '100%',
};
- ✓ agaro/legal-review-7b fine-tuned · ENG-049 v1.4
- · agaro/uw-classifier-3b distilled · ENG-048 v0.9
- ✓ agaro/claims-triage-7b LoRA · ENG-047 v2.1
- ✓ agaro/extraction-3b QLoRA · ENG-045 v1.0
Evals · CI
Custom evals you run continuously, so model regressions are caught in CI, not in the field.
// Evals · CI
// Custom evals you run continuously, so model regressions are caught in CI, not in the field.
export const evals_ci = {
eval_suites: '142',
coverage: '84%',
pass_rate: '98.4%',
regressions_caught: '4',
};
- ✓ legal-review · safety 482/482 · 0 regressions 4m 12s
- ✓ uw-classifier · accuracy 142/142 · 0 regressions 1m 48s
- ✓ claims-triage · jailbreak 88/88 · 0 successful 6m 18s
- ✓ extraction · pii 4,128 docs · 0 leaks 14m
Builds
CI pipelines, build artefacts, and deploys for every engagement — containers, IaC, and runbooks shipped together.
// Builds
// CI pipelines, build artefacts, and deploys for every engagement — containers, IaC, and runbooks shipped together.
export const builds = {
builds_24h: '142',
build_time_avg: '4m 11s',
deploys: '12',
crash_free: '99.94%',
};
- ✓ agaro/operator-console#1840 staging deploy 4m 12s
- ✓ agaro/legal-rag#982 prod deploy 3m 28s
- · agaro/uw-svc#412 integration tests running
- ✓ agaro/claims-api#284 lint + type 1m 12s
Data pipelines
Retrieval, embeddings, ingestion, and training pipelines — wired into your sources with backpressure and replay.
// Data pipelines
// Retrieval, embeddings, ingestion, and training pipelines — wired into your sources with backpressure and replay.
export const pipelines = {
active_pipelines: '24',
events_24h: '14M',
embedding_rate: '4.2K/s',
vector_store: '88GB',
};
- ✓ legal-rag · ingest 4,128 docs/d pgvector
- ✓ uw-features · CDC Postgres → feature store continuous
- ✓ claims-eval · train weekly · LoRA Sun 02:00
- ✓ extraction · drift detect continuous 14d window
Handover
Architecture docs, ADRs, runbooks, and 90-day support tail — knowledge transfer baked in from week one.
// Handover
// Architecture docs, ADRs, runbooks, and 90-day support tail — knowledge transfer baked in from week one.
export const handover = {
engagements_transferring: '4',
pair_sessions_30d: '24',
runbooks: '14',
90_day_tail: '3 active',
};
- ✓ ENG-047 · Claims triage 90% transferred · pair wk 12 tail wk 1
- ✓ ENG-049 · Legal review Architecture review wk 8 on plan
- ✓ ENG-045 · Extraction Runbook drafted wk 11
- ✓ ENG-040 · Drone routing 90-day tail · 60d remaining support
What this module actually does in production.
Domain-tuned models
Fine-tuning, distillation, and adapter training on your data — including parameter-efficient methods that fit your inference budget.
Agent systems
Multi-step, tool-using agents with planning, verification, and the supervision loops your operators trust.
Evaluation harnesses
Custom evals you run continuously, so model regressions are caught in CI, not in the field.
Safety & red-team
Adversarial testing against jailbreaks, prompt injection, and the failure modes specific to your domain.
Deployment-ready code
We ship containers, infrastructure-as-code, runbooks, and the documentation your SRE team needs to operate it.
Knowledge transfer
Pair with your engineers from week one. By the end, your team owns and operates what we built together.
Engineered to a standard, not a slogan.
Modules that compose with this one.
What buyers ask about custom ai software
— before they sign.
Deploy custom ai software
in one engagement.
A 30-day pilot will show you the integration shape, the operator experience, and the audit trail your accreditor will ask about — delivered by a senior engineering team that ships AI to production.
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