Anthropic Partner Network member

We embed with your team
and ship AI into the workflows
that run your business.

Quoting, scheduling, billing, delivery — production systems in your stack. Measured in cycle time, not slideware.

Built in your environment. You own the code. Fixed price when the scope is clear, a dedicated squad when it isn't. 5.0/5 on Clutch

Trusted by teams that run on us

What we do

Three practices. One team.

Custom Software, our largest practice. Cloud and DevOps. AI. Agent governance runs across all three.

Custom Software

The software that runs your company internally: operations platforms, ERP integrations, custom applications. Our largest practice.

integrations/erp-sync.ts

Custom Software

01import { SalesforceClient } from '@crm/salesforce'
02import { SAPClient } from '@erp/sap'
03import { OrderSchema } from './schemas'
04
05export async function syncOrder(orderId: string) {
06  const order = await SalesforceClient.getOrder(orderId)
07  const validated = OrderSchema.parse(order)
08  const result = await SAPClient.createOrder({
09    externalId: validated.id,
10    lineItems: validated.items,
11    customer: validated.accountRef
12  })
13  // bidirectional sync — write ERP order ID back to CRM
14  await SalesforceClient.updateOrder(orderId, {
15    erpOrderId: result.id, status: 'synced'
16  })
17}

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Cloud and DevOps

The cloud and platform engineering underneath it: CI/CD, infrastructure as code, observability. So what ships keeps working.

infrastructure/main.tf

Cloud & DevOps

01module "eks_cluster" {
source  = "terraform-aws-modules/eks/aws"
version = "~> 20.0"
cluster_name    = var.cluster_name
cluster_version = "1.30"
enable_irsa     = true
vpc_id          = module.vpc.vpc_id
subnet_ids      = module.vpc.private_subnets
09}
10
11resource "aws_rds_instance" "main" {
instance_class  = "db.t3.micro" # dev only
instance_class  = "db.r6g.large" # prod
multi_az        = true
storage_encrypted = true
engine          = "postgres"
17}

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Featured

AI

AI accelerates. It does not plug gaps. If you have gaps, it will surface them and make them worse. We find where AI pays off, set the guardrails, and build it into the systems you already own.

quoting/rfq-handler.ts

AI Engineering

01import { parseRFQ } from './parser'
02import { ERP } from './erp-client'
03import { AIQuoter } from '@nextlink/ai'
04
05export async function handleRFQ(rfq: RFQDocument) {
06  const parsed = await parseRFQ(rfq)
07  const quote = await manualEstimate(parsed) // 4.5h
08  const draft = await AIQuoter.draft(parsed, rules) // 18min
09  const approved = await humanReview(draft)
10  // human-in-the-loop — estimator approves before ERP write
11  return ERP.createQuote({
12    lineItems: parsed.items,
13    pricing: approved.pricing,
14    confidence: draft.score,
15    status: 'pending_review'
16  })
17}

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AI Quoting Accelerator

How long does a quote take you?

One quoting workflow, end to end: the system reads the RFQ, drafts the quote with your pricing logic, and routes it to your estimator for approval — then writes back to your ERP.

96%

reduction in quoting search time

CADDi, 2026

30–40%

shorter quote cycle times

Deloitte

4 weeks

to a scored, priced plan for your quoting workflow

AI Value Assessment, from $10,000

Those numbers come from rigid products and Fortune 500 programs. We build the same capability around your pricing logic, in your systems, at mid-market price.

Start with an AI Value Assessment → See the Quoting Accelerator →

Case studies

Real numbers from real engagements.

How we work

Embed. Ship. Measure.

Embed

Senior engineers join your team — your repos, your stack, your security model.

Ship

Production in weeks, not quarters. Human-in-the-loop until the accuracy data says otherwise.

Measure

Success is a number you already track — cycle time, win rate, hours saved — agreed up front.

Our own first case study

We run on what we sell.

Our sales pipeline runs on an AI intelligence system we built. Our inbox, Slack, and ticket triage are agentic. When we propose AI in your operations, we're describing how we already run ours.

quoting/rfq-handler.ts

Embed → Ship

− before

01import { parseRFQ } from './parser'
02import { ERP } from './erp-client'
03
04export async function handleRFQ(
05  rfq: RFQDocument
06) {
07  const parsed = await parseRFQ(rfq)
08  // estimator manually builds quote
09  const quote = await
10    manualEstimate(parsed)
11  // avg 4.5 hours per quote
12
13  return ERP.createQuote({
14    lineItems: parsed.items,
15    pricing: quote.pricing,
16    status: 'draft'
17  })
18}

+ after

01import { parseRFQ } from './parser'
02import { ERP } from './erp-client'
03import { AIQuoter } from '@nextlink/ai'
04export async function handleRFQ(
05  rfq: RFQDocument
06) {
07  const parsed = await parseRFQ(rfq)
08  // AI drafts quote, human approves
09  const quote = await
10    AIQuoter.draft(parsed, pricingRules)
11  // avg 18 min — 94% confidence
12
13  return ERP.createQuote({
14    lineItems: parsed.items,
15    pricing: quote.pricing,
16    aiConfidence: quote.confidence,
17    status: 'pending_review'
18  })
19}

Tell us which workflow is the bottleneck.

We'll tell you what AI can fix — and what it can't.

Book a call See the work

We embed with your team and ship AI into the workflows that run your business.

Three practices. One team.

Custom Software

Cloud and DevOps

AI

How long does a quote take you?

Real numbers from real engagements.

Embed. Ship. Measure.

Embed

Ship

Measure

We run on what we sell.

Tell us which workflow is the bottleneck.

We embed with your team
and ship AI into the workflows
that run your business.