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AI-native software engineering

Replace SaaS. Own Your Advantage.

Conseiltek deploys elite Forward Deployed Engineers to turn expensive SaaS, fragmented workflows, and high-value operational problems into secure, AI-native software built around your business.

What we do

Replace. Embed. Accelerate. Own.

Four things have to be true for owned software to beat rented software. They are the four things we are hired for, and they happen in this order.

01

Replace

Consolidate costly SaaS and manual workflows into purpose-built applications.

We take the licence line items, and the spreadsheet-and-email work that happens between them, and consolidate both into one application built for the workflow. The test is economic before it is technical: what the contract costs, how much of the product you actually use, and what it costs to build and operate the replacement.

02

Embed

Put Forward Deployed Engineers next to the business problem, not behind layers of handoffs.

Our engineers work in your repository, your standup and your incident channel, alongside the people who do the work. No requirements relay, no delivery centre in another timezone, and no change request between noticing a problem and fixing it.

03

Accelerate

Prototype quickly, integrate deeply, and move from concept to production.

A working slice in weeks, deployed into a real environment and wired to the systems and identity you already run. Progress is measured against a signed parity matrix rather than a burndown chart, and the prototype is built on the path that reaches production rather than beside it.

04

Own

Create durable software capabilities designed around your data, workflows, and competitive advantage.

The repository, the infrastructure-as-code, the data and the roadmap are yours, in your cloud account, from the first commit. Software shaped around how your business actually operates is an asset on your side of the contract, and it stops being a renewal conversation.

The economics

One contract, costed honestly.

SaaS sprawl is an arithmetic problem before it is an engineering problem, so this is the whole argument on the cheapest example in Techtons. Every figure below is a published list price with the date we checked it, or an infrastructure estimate with the assumptions written down.

Rented

Monday.com — Work Management, Pro

$91,200/ year

400 seats × $19 per seat per month. Recurring, forever, with no asset at the end of it. Viewers cost the same as contributors.

List price checked 2026-09-05 · monday.com/pricing

Owned

Cadence — running in your AWS account

$9,360/ year

Infrastructure only, 400 seats, production and non-production, single region. Unlimited viewer seats, because a database row does not have a price.

Plus the build: 8 weeks, 2 engineers. Itemised in the Cadence cost model.

$81,840

Difference in year one running cost, before the build is counted.

~14 mo

Typical payback at this size, including the build. Longer below 150 seats.

0

Renewal conversations. The schema, the data and the roadmap are yours.

Below roughly 150 seats this arithmetic usually does not work, and we will say so. Assess Your SaaS Stack against your own numbers →

Core offers

Four offers. One engineering company.

Everything Conseiltek sells sits under one of these four. The finer-grained practices underneath each one are the work that makes it real, and each has its own page with the deliverables, the phases and the cases where you should not buy it.

01

SaaS Replacement

Identify the applications and manual workflows worth replacing, then build the replacement.

High recurring licence costs, overlapping products, spreadsheet-driven workflows, weak workflow fit, per-user pricing and vendor lock-in are the opportunities we look for. We establish parity on what you actually use, migrate the data, run in parallel, and cut over.

Practices under this offer

02

Forward Deployed Engineering

Engineers who work directly with your teams, at the intersection of software, AI, data, product and operations.

An FDE learns the actual workflow, works alongside your domain experts, turns ambiguous business problems into technical systems, and stays until the thing runs in production and someone can measure it. They are not developers for hire.

Practices under this offer

03

AI-Native Application Development

Applications where AI is part of the architecture and the workflow rather than a bolt-on feature.

Agentic workflows, enterprise search and retrieval, document processing, extraction and classification, knowledge assistants, model integration and orchestration, and the human-in-the-loop design that makes any of it usable. With evaluation, observability, security and governance attached, because that is what separates a demo from a deployment.

Practices under this offer

04

Enterprise Integration and Modernization

The work that has to be true underneath everything else.

APIs and microservices, cloud-native development, legacy modernisation, data integration, identity and access, workflow orchestration, web and mobile applications, platform engineering, and production support with continuous enhancement.

Practices under this offer

All 8 practices in full →

The SaaS replacement approach

Discover. Rationalize. Design. Build. Integrate. Deploy. Operate. Improve.

Eight steps, always in this order. The second one is the step most firms skip, and it is the one that decides whether the other seven are worth doing at all.

01

Discover

Read the incumbent rather than the sales deck: usage telemetry, the admin export, the permission model, every integration seam, and the five people who live in the tool.

02

Rationalize

Separate the commodity from the advantage. Overlapping products get consolidated, unused surface area gets dropped, and anything better bought than built is named now rather than in month five.

03

Design

A parity matrix your decision-maker signs, an explicit out-of-scope list, a target architecture for AWS and Azure, and the cutover criteria agreed before any application code exists.

04

Build

Start from a Techtons reference implementation rather than an empty repository. Deployed to your non-production environment on day one of the build and redeployed continuously after that.

05

Integrate

Identity, data, events and the downstream systems that made the old tool sticky, rebuilt natively against your existing enterprise platforms so the seams belong to you as well.

06

Deploy

The data migration is rehearsed before a cutover date is promised. Then a parallel run, reconciliation, and a cutover with a rollback that has actually been tested.

07

Operate

SLOs, on-call, patching, upgrades, capacity and cost review, running in your cloud account. Priced per system, cancellable, and designed to hand back to your team.

08

Continuously Improve

The workflow keeps moving, so the software does. Each release is measured against adoption and cycle time rather than a feature count, and the next replacement opportunity is identified from the same data.

Forward deployed engineering

Engineers at the point of impact, not behind a statement of work.

A Conseiltek Forward Deployed Engineer is a multidisciplinary engineer who works directly with your teams to discover, build, deploy and continuously improve software around a high-value business problem. Never staff augmentation, never a ticket queue, never capacity sold by the month.

01

Embed

In your repository, your standup and your incident channel, next to the people who do the work.

02

Understand

Learn the actual workflow from the operators, not the process document. Argue with the domain expert until the model is right.

03

Prototype

Something running in days, against real data, so the conversation is about a system rather than a slide.

04

Integrate

Connect the enterprise systems, identity and data that the workflow actually touches, including the ones missing from the diagram.

05

Productionize

Security, observability, tests, runbooks and a deployment path. The demo and the production system are the same repository.

06

Measure

Adoption, cycle time, cost and quality. If the number does not move, the engineering did not land.

07

Iterate

Keep going after launch. The first version is a hypothesis about the workflow, and workflows answer back.

AI-native engineering

AI designed into the architecture, not bolted onto the interface.

AI is how we build in weeks instead of quarters, and it is also what we build. In the applications we ship it sits inside the workflow — extraction, classification, retrieval over your own data, agentic steps with a human in the loop — with evaluation, observability and governance attached, because that is what separates a demo from a deployment.

Readiness assessment

Where the work actually is, which of it AI is good at today, and what your data and access model will let you do.

Applications, not pilots

Agentic workflows, enterprise search and retrieval, document processing, extraction and classification, built into software people use to do their jobs.

Process redesign

The gains come from changing the process, not from adding a chatbot to it. We redesign the workflow, then automate the parts worth automating.

Enablement

Internal champions, role-specific training, an internal prompt and pattern library, and office hours until it sticks.

Measurement

Adoption measured in changed workflows and cycle time, not seat counts. Reported monthly to the board.

Techtons by Conseiltek

One reference application. Every day.

We do not publish a logo wall. Techtons is our open library, and it is a public repository rather than a portfolio page. Each application ships with runnable code, an AWS architecture with Terraform, an Azure architecture with Bicep, a parity matrix against the product it replaces, and a cost model with the arithmetic shown. Apache-2.0, all of it.

All 37 applications

3 published · 34 scheduled through Oct 11, 2026 · github.com/ConseilTek-Tektons

The principle

Buy commodity. Build advantage.

We do not think every SaaS product should be rebuilt, and a firm that did would be selling you something. Replace SaaS when the economics, the workflow differentiation, the integration burden or the strategic value justify ownership. Otherwise keep the licence and put the engineering somewhere it earns more.

How we test it — ten dimensions

Annual licence cost

What the contract actually costs at renewal, not at first signature.

Integration cost

What you pay in connectors, middleware and manual reconciliation to make it fit.

Feature utilisation

How much of the product surface anyone has touched in ninety days.

Workflow fit

How much of your process exists to satisfy the tool rather than the business.

Data ownership

Whether you can get the data out completely, on demand, in a usable shape.

Vendor lock-in

What it would cost to leave, and how long the exit would take.

Process differentiation

Whether this workflow is how you compete or simply how everyone does it.

AI opportunity

Whether the work inside the tool is work a model could do against your own data.

Build and operate cost

The honest total: the build, the cloud bill, and the team that runs it in year three.

Time to value

How long until the replacement is doing real work, measured against the next renewal date.

A two-week Discover scores one contract against all ten and writes the answer down, including when the answer is no. The first three you can run yourself. Assess Your SaaS Stack →

Where this does not work

Four times we will tell you to keep paying the vendor.

Every application in Techtons has a parity table with at least two rows where the honest answer is no. That is deliberate. These are the four cases where replacement is the wrong call, and we would rather say it now than in month five.

You are under about 150 seats

Per-seat pricing is genuinely cheap at small scale. The build does not pay back inside a sensible horizon. Come back when you are bigger, or when the vendor raises prices.

The vendor attestation is the product

If what you are really buying is a SOC 2 report to hand your auditor, or a court-tested e-signature record, or payroll certified in 40 countries, keep buying it. We cannot manufacture that.

The value is in the network

A supplier network, a shared deliverability reputation, an app marketplace with two hundred integrations. These are not features. They are other people, and we cannot rebuild them.

Nobody will own it afterwards

Owned software needs an owner. If there is no team and no budget line to run it in year three, the honest answer is a licence, not a repository.

How delivery runs

Discover. Prove. Deploy. Scale.

This is the delivery sequence on every engagement, whatever the commercial shape. Each stage has an exit that is a document or a running system rather than a status report, and you can stop at the end of any of them.

01

Discover

Map workflows, systems, spend, pain points and opportunity.

Two weeks, fixed price, ending in a document you keep whether or not you continue: what the incumbent costs, what you use, where the manual work sits, and which opportunity is worth taking first.

02

Prove

Build a focused prototype or production slice that validates the technical and the economic assumptions.

One slice, deployed, against real data and real users. If the assumptions do not hold, this is where you find out, and it is the cheapest place in the whole sequence to find out.

03

Deploy

Integrate with enterprise systems, security, data and operations.

Identity, downstream systems, the data migration, the parallel run and the cutover. Production is the point at which the work counts, so it is planned from week one rather than appended.

04

Scale

Expand the capability, harden the platform, drive adoption, and identify the next replacement opportunity.

Adoption measured in changed workflows, the platform hardened against what production has taught us, and the next candidate chosen from evidence rather than from the renewal calendar.

How you contract

Three commercial models. The same engineers in all three.

Separate axis from the delivery sequence above: Discover, Prove, Deploy and Scale describe how the work runs, and these three describe who holds the keyboard and where the risk sits.

01

Guide

You have a dev team. We hand them the blueprint.

Reference architecture, the code, the infrastructure-as-code, the migration plan and a weekly working session with the engineer who built it. Your team does the building. We make sure they are not discovering the hard parts in production.

  • Full reference implementation under Apache-2.0
  • AWS Terraform and Azure Bicep, both maintained
  • Architecture review and written ADRs
  • Weekly 90-minute working session with an FDE
  • Migration runbook and rollback plan
  • Async access to the engineering channel

Fixed monthly. 3-month minimum.

You have engineers and you want the blueprint, not the builders.

02

Join

Hire a Forward Deployed Engineer. They sit in your team.

One of our engineers joins your standup, your repo and your on-call rotation. They are measured on your outcome, not on hours booked. They write code in your codebase from week one and leave documentation behind them.

  • A named senior engineer, not a rotating bench
  • In your repo, your standup, your Slack
  • Everything in Guide, plus hands on keyboard
  • Pairing and code review that upskills your team
  • A written handover from day one, not day last
  • Replaceable on two weeks notice, either direction

Monthly per engineer. 3-month minimum, 30-day exit.

You have engineers, but not the specific depth this needs.

03

Deliver

We take it end to end and hand over the keys.

Discovery, build, migration, cutover, production run, handover. We own the outcome and the date. At the end you get the repository, the infrastructure, the runbooks and a team trained to run it, or we keep running it for you.

  • Fixed scope and a fixed date, agreed before we start
  • A pod: FDE lead, engineers, and a platform engineer
  • Data migration from the incumbent, with reconciliation
  • Parallel run and a rehearsed cutover with rollback
  • 30 days of hypercare after go-live
  • Optional Run agreement: we operate it, you own it

Fixed price per phase. Run priced separately.

You want the outcome, not the project.

Pick one contract. We will show you the replacement.

A two-week assessment: we take your single most expensive SaaS line item, establish what you actually use, and come back with a parity matrix, an architecture for AWS and Azure, a cost model and a delivery plan. Fixed price. If the answer is keep buying it, we will tell you that.